数学建模美赛三等奖论文
数学建模三等奖

数学建模三等奖1.引言1.1 概述概述部分的内容可以按以下方式进行编写:引言部分是写作的开端,旨在引起读者的兴趣并为之后的内容做一个铺垫。
在这一部分中,我们可以简要介绍数学建模三等奖的背景和意义,为读者提供一个整体的认识。
数学建模三等奖是一个非常重要的奖项,它旨在表彰在数学建模领域中取得优秀成绩的个人或团队。
这是一个具有一定难度和挑战性的竞赛,参赛者需要运用数学知识与技巧,结合实际问题,进行建模分析和解决方案的提出。
数学建模三等奖的获得者通常具备扎实的数学基础知识,熟悉数学建模的方法和步骤,并且具备较强的分析和创新能力。
通过参与数学建模的比赛,获得三等奖的学生们能够在实践中提高自己的学习能力和解决问题的能力,并在数学领域中取得了一定的突破和成就。
此外,数学建模比赛不仅对参赛者个人的能力提出了要求,也对团队合作和协作能力提出了挑战。
在参赛过程中,团队成员需要相互合作、共同分工,并提出相应的解决方案。
通过团队成员之间的交流和合作,能够促进个人的进步和团队的发展。
数学建模三等奖对参赛者的未来学习和职业发展也具有积极的影响。
这一荣誉可以为参赛者提供更多的学习机会和交流平台,拓宽参赛者的视野,并为将来的教育和职业发展提供有力的支持。
总的来说,数学建模三等奖是一个具有重要意义的奖项,对于学生们的学习能力、解决问题的能力和团队合作能力都提出了较高的要求。
获得这一奖项不仅可以证明参赛者在数学建模领域的才华和能力,还可以为参赛者在学习和职业发展中开辟更广阔的道路。
1.2文章结构文章结构:本篇文章主要分为引言、正文和结论三个部分。
引言部分包括概述、文章结构和目的三个方面。
在概述中,我们将简要介绍数学建模竞赛及其重要性。
数学建模竞赛是基于数学方法和技巧对实际问题进行分析和求解的比赛,对于培养学生的数学建模能力和解决实际问题的能力具有重要意义。
在文章结构中,我们将列出本文的整体结构,以便读者了解文章的组织形式。
在目的部分,我们说明本文撰写的目的是为了介绍数学建模竞赛中获得三等奖的相关情况,并对其中一些要点进行详细探讨。
数学建模大赛论文范文

数学建模大赛论文范文标题:气候变化与全球粮食安全关联性的数学建模研究摘要:气候变化对全球粮食安全造成了极大的影响,然而,气候变化与全球粮食安全的关联性尚未得到全面的研究和评估。
本研究基于数学建模的方法,探讨了气候变化与全球粮食安全之间的关联性,并提出了相应的策略和措施,以应对气候变化对全球粮食安全的威胁。
1.引言粮食安全是国家乃至全球经济和社会稳定的重要基础。
然而,气候变化给全球粮食生产和供应带来了巨大的挑战。
为了准确评估气候变化对全球粮食安全的影响,本文利用数学建模方法进行研究。
2.数据收集与整理本研究首先收集了过去几十年来的气象数据和全球粮食产量数据,包括气温、降雨量、CO2浓度和粮食作物产量等。
然后,根据这些数据进行整理和统计分析,探索气候变化与全球粮食安全之间的关联性。
3.模型建立基于收集到的数据,我们建立了一个数学模型,通过对气候变化对全球粮食作物的生育期和生长条件的影响进行数值模拟。
模型考虑了温度、降水、CO2浓度等因素对不同作物的生理和生态效应,以及这些因素之间的相互作用。
4.模型验证为了验证建立的模型的准确性和可靠性,本研究以过去几十年的数据为基础,进行了模型的验证。
通过与实际观测数据进行对比,验证了模型的合理性和适用性。
5.结果与讨论通过模拟和分析,我们发现气候变化对全球粮食作物的产量产生了显著影响。
温度升高、降雨分布不均和CO2浓度增加等因素导致了粮食产量的减少和不稳定性增加。
此外,不同地区的气候变化对粮食作物的影响程度也存在差异。
6.策略与措施针对气候变化对全球粮食安全的威胁,本研究提出了一些相应的策略和措施。
首先,应加强全球气象监测和预测能力,提前做出应对措施。
其次,通过技术创新和改良,提高农作物的耐逆性和抗病虫害能力。
此外,鼓励农民采用可持续农业方式,减少对化肥和农药的依赖。
7.结论本研究基于数学建模的方法,全面探讨了气候变化对全球粮食安全的影响,并提出了相应的策略和措施。
建模美赛获奖范文

建模美赛获奖范文全文共四篇示例,供读者参考第一篇示例:近日,我校数学建模团队在全国大学生数学建模竞赛中荣获一等奖的喜讯传来,这是我校首次在该比赛中获得如此优异的成绩。
本文将从建模过程、团队合作、参赛经验等方面进行详细介绍,希望能为更多热爱数学建模的同学提供一些借鉴和参考。
让我们来了解一下比赛的背景和要求。
全国大学生数学建模竞赛是由中国工程院主办,旨在促进大学生对数学建模的兴趣和掌握数学建模的基本方法和技巧。
比赛通常会设置一些实际问题,参赛队伍需要在规定时间内通过建立数学模型、分析问题、提出解决方案等步骤来完成任务。
最终评选出的优胜队伍将获得一等奖、二等奖等不同级别的奖项。
在本次比赛中,我们团队选择了一道关于城市交通拥堵研究的题目,并从交通流理论、路网优化等角度进行建模和分析。
通过对城市交通流量、拥堵原因、路段限制等方面的研究,我们提出了一种基于智能交通系统的解决方案,有效缓解了城市交通拥堵问题。
在展示环节,我们通过图表、数据分析等方式清晰地呈现了我们的建模过程和成果,最终赢得了评委的认可。
在整个建模过程中,团队合作起着至关重要的作用。
每个成员都发挥了自己的专长和优势,在分析问题、建模求解、撰写报告等方面各司其职。
团队内部的沟通和协作非常顺畅,大家都能积极提出自己的想法和看法,达成共识后再进行实际操作。
通过团队合作,我们不仅完成了比赛的任务,也培养了团队精神和合作能力,这对我们日后的学习和工作都具有重要意义。
参加数学建模竞赛是一次非常宝贵的经历,不仅能提升自己的数学建模能力,也能锻炼自己的解决问题的能力和团队协作能力。
在比赛的过程中,我们学会了如何快速建立数学模型、如何分析和解决实际问题、如何展示自己的成果等,这些能力对我们未来的学习和工作都将大有裨益。
在未来,我们将继续努力,在数学建模领域不断学习和提升自己的能力,为更多的实际问题提供有效的数学解决方案。
我们也希望通过自己的经验和教训,为更多热爱数学建模的同学提供一些指导和帮助,共同进步,共同成长。
全国数学建模省三等奖

型进行了进一步分析, 寻找出了模型所存在的缺点, 我们对这些缺点进行了分析和研究, 在得到某些信息的前提下, 我们建立了金属污染物扩散模型。 确定了污染源的具体位置, 从而来研究城市地质环境的演变模式。
三、模型假设
1、假设收集样本时均采取随机取样,统计样本点的浓度时无误差。 2、假设收集样本之后的期间内均没有大型自然灾害以及大兴土木的现象发生。 3、假设附件中给出的数据均客观真实。 4、假设采集样本之后短期内不会出现降雨,降雪等天气。 。 5、假设城市短期内没有大规模的的人类迁移活动,发展均平稳发展。 6、假设在计算综合污染指数时,不考虑各个单项重金属元素的权重。 7、假设土壤接近中性,忽略土质差异。
5
协方差为零,几何上就是这两个主成分的方向正交。具体确定各个主成分的方法如下: 设 zi 表示第i 个主成分,i = 1,2,…,n,可设 z1 = c11 x1 + c12 x2 + + c1n xn = z2 c21 x1 + c22 x2 + + c2n xn zm = cm1 x1 + cm 2 x2 + + cmn xn
2 其中对每一个i ,均有 ci21 + ci22 + + cip = 1 且 (ci1 , ci 2 , , cip ) 使得 Var ( Z1 ) 的值达到最
大; (c21 , c22 , , c2 p ) 不仅垂直于 (c11 , c12 ,, c1 p ) ,而且使 Var ( Z 2 ) 的值达到最大; (c31 , c32 , , c3 p ) 同时垂直于 (c11 , c12 , , c1 p ) 和 (c21 , c22 , , c2 p ) ,并使 Var ( Z3 ) )的值达到最 大。 1)对原始数据进行标准化处理 表1 原始数据标准化处理 样本\指标 x1 x2 1 Y11 Y12 2 Y21 Y22 3 Y31 Y32 … m Ym1 Yij − Y j Sj 1 m ∑ Yij m i =1 Ym2
数学建模大赛论文范文

数学建模大赛论文范文一、问题重述在约10,000米高空的某边长160公里的正方形区域内,经常有若干架飞机作水平飞行。
区域内每架飞机的位置和速度向量均由计算机记录其数据,以便进行飞行管理。
当一架欲进入该区域的飞机到达区域边缘时,记录其数据后,要立即计算并判断是否会与区域内的其它飞机发生相撞。
如果发生相撞,则应计算如何调整各架(包括新进入的)飞机的飞行方向角,以避免碰撞。
现假设条件如下:(1) 不相撞的标准为任意两架飞机的距离大于8公里; (2) 飞机飞行方向角调整的幅度不应超过30度; (3) 所有飞机的飞行速度均为每小时800公里;(4) 进入该区域的飞机在到达区域边缘时,与区域内飞机的距离应在60公里以上;(5) 最多需考虑6架飞机;(6) 不必考虑飞机离开此区域后的情况。
请你对这个避免碰撞的飞行管理问题建立数学模型,列出计算步骤,对以下数据进行计算(方向角误差不超过0.01度),要求飞机飞行方向角调整的幅度尽量小。
设该区域4个顶点的坐标为(0,0),(160,0),(160,160),(0,160)。
记录数据为:注:方向角指飞行方向与x轴正向的夹角。
二、问题分析此问题很容易想到以飞机调整的飞行角度平方和作为目标函数,而以每两架飞机之间的最小距离不超过8km,各飞机飞行角度调整的值不超过30°为约束条件。
如此得出的是一个非线性模型,在计算上可能会复杂些,但一目了然。
三、符号说明t表示表示时间;; xi,yi分别表示第i架飞机的横纵坐标(问题中已给出);i表示第i架飞机的飞行方向角(问题中已给出)dij(t)表示t时刻第i架飞机与第j架飞机间的距离;。
v表示飞机的飞行高度(v800)四、模型的建立由题意可知,目标函数是6f i2i1约束条件为Dij mindij264 和it06,i,j1,2,,6,i j其中dij(t)(xi xj vt(cos(i i)cos(j j))) 22(yi yj vt(sin(i i)sin(j j)))2利用微积分的知识可求出Dij,由2d(dij)dt这里a0tba(xi xj)(cos(i i)cos(j j))(yi yj)(sin(i i)sin(j j))b v[(cos(i i)cos(j j))2(sin i(i2))])s in(jj将t代入即可求出Dij。
数学建模 美赛获奖论文

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2010 Mathematical Contest in Modeling (MCM) Summary Sheet
(Attach a copy of this page to each copy of your solution paper.)
Keywords:simple harmonic motion system , differential equations model , collision system
美赛数模论文
MCM 2015 Summary Sheet for Team 35565For office use onlyT1________________ T2________________ T3________________ T4________________Team Control Number35565Problem ChosenBFor office use onlyF1________________F2________________F3________________F4________________ SummaryThe lost MH370 urges us to build a universal search plan to assist searchers to locate the lost plane effi-ciently and optimize the arrangement of search plans.For the location of the search area, we divided it into two stages, respectively, to locate the splash point and the wreckage‟s sunk point. In the first stage, we consider the types of crashed aircraft, its motion and different position out of contact. We also consider the Earth‟s rotation, and other factors. Taking all these into account, we establish a model to locate the splash point. Then we apply this model to MH370. we can get the splash point in the open water is 6.813°N 103.49°E and the falling time is 52.4s. In the second stage, considering resistances of the wreckage in different shapes and its distribution affected by ocean currents, we establish a wreckage sunk point model to calculate the horizontal displacement and the angle deviation affected by the ocean currents. The result is 1517m and 0.11°respectively. Next, we extract a satellite map of submarine topography and use MATLAB to depict seabed topography map, determining the settlement of the wreckage by using dichotomy algorithm under different terrains. Finally, we build a Bayesian model and calculate the weight of corresponding area, sending aircrafts to obtain new evidence and refresh suspected wreckage area.For the assignment of the search planes, we divide it into two stages, respectively, to determine the num-ber of the aircraft and the assignment scheme of the search aircraft. In the first stage, we consider the search ability of each plane and other factors. And then we establish global optimization model. Next we use Dinkelbach algorithm to select the best n search aircrafts from all search aircrafts. In the second stage, we divide the assignment into two cases whether there are search aircrafts in the target area. If there is no search aircraft, we take the search area as an arbitrary polygon and establish the subdivision model. Considering the searching ability of each plane, we divide n small polygons into 2n sub-polygons by using NonconvexDivide algorithm, which assigns specific anchor points to these 2n sub-polygons re-spectively. If there exist search aircrafts, we divide the search area into several polygons with the search aircrafts being at the boundary of the small polygons. To improve search efficiency, we introduce” ma x-imize the minimum angle strategy” to maximize right-angle subdivision so that we can reduce the turning times of search aircraft. When we changed the speed of the crashed plane about 36m/s, the latitude of the splash point changes about 1°.When a wreck landing at 5.888m out from the initial zone, it will divorce from suspected searching area, which means our models are fairly robust to the changes in parameters. Our model is able to efficiently deal with existing data and modify some parameters basing the practical situation. The model has better versatility and stability. The weakness of our model is neglect of human factors, the search time and other uncontrollable factors that could lead to deviation compared to practical data. Therefore, we make some in-depth discussions about the model, modifying assumptions establish-Searching For a Lost PlaneControl#35565February 10, 2014Team # 35565 Page 3 of 47 Contents1 Introduction (5)1.1 Restatement of the Problem (5)1.2 Literature Review (6)2 Assumptions and Justifications (7)3 Notations (7)4 Model Overview (10)5 Modeling For Locating the Lost Plane (10)5.1 Modeling For Locating the Splash Poin t (11)5.1.1 Types of Planes (11)5.1.2 Preparation of the Model—Earth Rotation (12)5.1.3 Modeling (13)5.1.4 Solution of The Model (14)5.2 Modeling For Locating Wreckage (15)5.2.1 Assumptions of the Model (16)5.2.2 Preparation of the Model (16)5.2.3 Modeling (21)5.2.4 Solution of the Model (25)5.3 Verification of the Model (26)5.3.1 Verification of the Splash Point (26)5.3.2 Verification of the binary search algorithm (27)6 Modeling For Optimization of Search Plan (29)6.1 The Global Optimization Model (29)6.1.1 Preparation of the Model (29)6.1.2 Modeling (31)6.1.3 Solution of the Model (31)6.2 The Area Partition Algorithm (33)6.2.1 Preparation of the Model (33)6.2.2 Modeling (34)6.2.3 Solution of the Model (35)6.2.4 Improvement of the Model (36)7 Sensitivity Analysis (38)8 Further Discussions (39)9 Strengths and Weaknesses (41)9.1 Strengths (41)9.2 Weaknesses (42)10 Non-technical Paper (42)1 IntroductionAn airplane (informally plane) is a powered, fixed-wing aircraft that is propelled for-ward by thrust from a jet engine or propeller. Its main feature is fast and safe. Typi-cally, air travel is approximately 10 times safer than travel by car, rail or bus. Howev-er, when using the deaths per journey statistic, air travel is significantly more danger-ous than car, rail, or bus travel. In an aircraft crash, almost no one could survive [1]. Furthermore, the wreckage of the lost plane is difficult to find due to the crash site may be in the open ocean or other rough terrain.Thus, it will be exhilarating if we can design a model that can find the lost plane quickly. In this paper, we establish several models to find the lost plane in seawater and develop an op-timal scheme to assign search planes to model to locate the wreckage of the lost plane.1.1 Restatement of the ProblemWe are required to build a mathematical model to find the lost plane crashed in open water. We decompose the problem into three sub-problems:●Work out the position and distributions of the plane‟s wreckage●Arrange a mathematical scheme to schedule searching planesIn the first step, we seek to build a model with the inputs of altitude and other factors to locate the splash point on the sea-level. Most importantly, the model should reflect the process of the given plane. Then we can change the inputs to do some simulations. Also we can change the mechanism to apply other plane crash to our model. Finally, we can obtain the outputs of our model.In the second step, we seek to extend our model to simulate distribution of the plane wreckage and position the final point of the lost plane in the sea. We will consider more realistic factors such as ocean currents, characteristics of plane.We will design some rules to dispatch search planes to confirm the wreckage and de-cide which rule is the best.Then we attempt to adjust our model and apply it to lost planes like MH370. We also consider some further discussion of our model.1.2 Literature ReviewA model for searching the lost plane is inevitable to study the crashed point of the plane and develop a best scheme to assign search planes.According to Newton's second law, the simple types of projectile motion model can work out the splash point on the seafloor. We will analyze the motion state ofthe plane when it arrives at the seafloor considering the effect of the earth's rotation,After the types of projectile motion model was established, several scientists were devoted to finding a method to simulate the movement of wreckage. The main diffi-culty was to combine natural factors with the movement. Juan Santos-Echeandía introduced a differential equation model to simplify the difficulty [2]. Moreover,A. Boultif and D. Louër introduced a dichotomy iteration algorithm to circular compu-ting which can be borrowed to combine the motion of wreckage with underwater ter-rain [3]. Several conditions have to be fulfilled before simulating the movement: (1) Seawater density keeps unchanged despite the seawater depth. (2) The velocity of the wreck stay the same compared with velocity of the plane before it crashes into pieces.(3) Marine life will not affect our simulation. (4) Acting forceof seawater is a function of the speed of ocean currents.However the conclusion above cannot describe the wreckage zone accurately. This inaccuracy results from simplified conditions and ignoring the probability distribution of wreckage. In 1989, Stone et.al introduced a Bayesian search approach for searching problems and found the efficient search plans that maximize the probability of finding the target given a fixed time limit by maintaining an accurate target location probabil-ity density function, and by explicitly modeling the target‟s process model [4].To come up with a concrete dispatch plan. Xing Shenwei first simulated the model with different kinds of algorithm. [5] In his model, different searching planes are as-sessed by several key factors. Then based on the model established before, he use the global optimization model and an area partition algorithm to propose the number of aircrafts. He also arranged quantitative searching recourses according to the maxi-mum speed and other factors. The result shows that search operations can be ensured and effective.Further studies are carried out based on the comparison between model andreality.Some article illustrate the random error caused by assumptions.2 Assumptions and JustificationsTo simplify the problem, we make the following basic assumptions, each ofwhich is properly justified.●Utilized data is accuracy. A common modeling assumption.●We ignore the change of the gravitational acceleration. The altitude of anaircraft is less than 30 km [6]. The average radius of the earth is 6731.004km, which is much more than the altitude of an aircraft. The gravitational accele-ration changes weakly.●We assume that aeroengine do not work when a plane is out of contact.Most air crash resulted from engine failure caused by aircraft fault, bad weather, etc.●In our model, the angle of attack do not change in an air crash and thefuselage don’t wag from side to side. We neglect the impact of natural and human factors●We treat plane as a material point the moment it hit the sea-level. Thecrashing plane moves fast with a short time-frame to get into the water. The shape and volume will be negligible.●We assume that coefficient of air friction is a constant. This impact is neg-ligible compared with that of the gravity.●Planes will crash into wreckage instantly when falling to sea surface.Typically planes travel at highly speed and may happen explosion accident with water. So we ignore the short time.3 NotationsAll the variables and constants used in this paper are listed in Table 1 and Table 2.Table 1 Symbol Table–ConstantsSymbol DefinitionωRotational angular velocity of the earthg Gravitational accelerationr The average radius of the earthC D Coefficient of resistance decided by the angle of attack ρAtmospheric densityφLatitude of the lost contact pointμCoefficient of viscosityS0Area of the initial wrecking zoneS Area of the wrecking zoneS T Area of the searching zoneK Correction factorTable 2 Symbol Table-VariablesSymbol DefinitionF r Air frictionF g Inertial centrifugal forceF k Coriolis forceW Angular velocity of the crash planev r Relative velocity of the crash planev x Initial velocity of the surface layer of ocean currentsk Coefficient of fluid frictionF f Buoyancy of the wreckagef i Churning resistance of the wreckage from ocean currents f Fluid resistance opposite to the direction of motionG Gravity of the wreckageV Volume of the wreckageh Decent height of the wreckageH Marine depthS x Displacement of the wreckageS y Horizontal distance of S xα Deviation angle of factually final position of the wreckage s Horizontal distance between final point and splash point p Probability of a wreck in a given pointN The number of the searching planeTS ' The area of sea to be searched a i V ˆ The maximum speed of each planeai D The initial distance from sea to search planeai A The search ability of each plane is),(h T L i The maximum battery life of each plane isi L The mobilized times of each plane in the whole search )1(N Q Q a a ≤≤ The maximum number of search plane in the searching zone T(h) The time the whole action takes4 Model OverviewMost research for searching the lost plane can be classified as academic and practical. As practical methods are difficult to apply to our problem, we approach theproblem with academic techniques. Our study into the searching of the lost plane takes several approaches.Our basic model allows us to obtain the splash point of the lost plane. We focus on the force analysis of the plane. Then we We turn to simple types of projectile motion model. This model gives us critical data about the movement and serves as a stepping stone to our later study.The extended model views the problem based on the conclusion above. We run diffe-rential equation method and Bayesian search model to simulate the movement of wreckage. The essence of the model is the way to combine the effect of natural factors with distribution of the wreckage. Moreover, using distributing conditions, we treat size of the lost plane as “initial wreckage zone” so as to approximately describe the distribution. Thus, after considering the natural factors, we name the distribution of wreckage a “wreck zone” to minimize searching zone. While we name all the space needed to search “searching zone”.Our conclusive model containing several kinds of algorithm attempts to tackle a more realistic and more challenging problem. We add the global optimization model and an area partition algorithm to improve the efficiency of search aircrafts according to the area of search zone. An assessment of search planes consisting of search capabili-ties and other factors are also added. The Dinkelbach and NonConvexDivide algo-rithm for the solutions of the results are also added.We use the extended and conclusive model as a standard model to analyze the problem and all results have this two model at their cores.5 Modeling For Locating the Lost PlaneWe will start with the idea of the basic model. Then we present the Bayesian search model to get the position of the sinking point.5.1 Modeling For Locating the Splash PointThe basic model is a academic approach. A typical types of projectile behavior con-sists of horizontal and vertical motion. We also add another dimension consider-ing the effect of the earth's rotation. Among these actions, the force analysis is the most crucial part during descent from the point out of contact to the sea-level. Types of plane might impact trajectory of the crashing plane.5.1.1 Types of PlanesWe classify the planes into six groups [7]:●Helicopters: A helicopter is one of the most timesaving ways to transfer be-tween the city and airport, alternatively an easy way to reach remote destina-tions.●Twins Pistons: An economical aircraft range suitable for short distance flights.Aircraft seating capacity ranging from 3 to 8 passengers.●Turboprops: A wide range of aircraft suitable for short and medium distanceflights with a duration of up to 2-4 hours. Aircraft seating capacity ranging from 4 to 70 passengers.●Executive Jets:An Executive Jet is suitable for medium or long distanceflights. Aircraft seating capacity ranging from 4 to 16 passengers●Airliners:Large jet aircraft suitable for all kinds of flights. Aircraft seatingcapacity ranging from 50 to 400 passengers.●Cargo Aircrafts:Any type of cargo. Ranging from short notice flights carry-ing vital spare parts up to large cargo aircraft that can transport any volumin-ous goods.The lost plane may be one of these group. Then we extract the characteristics of planes into three essential factors: mass, maximum flying speed, volume. We use these three factors to abstract a variety of planes:●Mass: Planes of different product models have their own mass.●Maximum flying speed: Different planes are provided with kinds of me-chanical configuration, which will decide their properties such as flying speed.●Volume: Planes of distinct product models have different sizes and configura-tion, so the volume is definitive .5.1.2 Preparation of the Model —Earth RotationWhen considering the earth rotation, we should know that earth is a non-inertial run-ning system. Thus, mobile on the earth suffers two other non-inertial forces except air friction F r . They are inertial centrifugal force F g and Coriolis force F k . According to Newton ‟s second law of motion, the law of object relative motion to the earth is:Rotational angular velocity of the earth is very small, about .For a big mobile v r , it suffers far less inertial centrifugal force than Coriolis force, so we can ignore it. Thus, the equation can be approximated as follows:Now we establish a coordinate system: x axis z axis pointing to the east and south re-spectively, y axis vertical upward, then v r , ω and F r in the projection coordinate system are as follows:⎪⎪⎩⎪⎪⎨⎧++=⋅⋅-⋅⋅=++=kdt dz j dt dy i dt dx m v k j w kF j F i F F r rz ry rx r φωφωcos sinφis the latitude of the lost contact point of the lost plane. Put equation 1-3 and equa-tion 1-2 together, then the component of projectile movement in differential equation is:ma FF F k g r=++srad ⋅⨯=-5103.7ωmamv F r r =+ω2⎪⎪⎪⎩⎪⎪⎪⎨⎧+⋅=+⋅=+⎪⎭⎫ ⎝⎛+⋅-=m F dt dx w dt z d m F dt dx w dt y d m F dt dz dt dy w dtx d rz ry rx φφφφsin 2cos 2sin cos 22222225.1.3 ModelingConsidering the effect caused by earth rotation and air draught to plane when crashing to sea level, we analyze the force on the X axis by using Newton ‟s second law, the differential equation on x y and axis, we can conclude:In conclusion, we establish the earth rotation and types of projectile second order dif-ferential model:()⎪⎩⎪⎨⎧+-⋅'⋅⋅=''-⋅'+⋅'⋅⋅-=''-⋅'⋅⋅=''m gf y w m z m f z x w m y m f y w m x m obj 321cos 2cos sin 2sin 2.φφφφAccording to Coriolis theorem, we analyze the force of the plane on different direc-tions. By using the Newton ‟s laws of motion, we can work out the resultant accelera-tion on all directions:⎪⎪⎪⎪⎪⎪⎪⎪⎩⎪⎪⎪⎪⎪⎪⎪⎪⎨⎧'+'+'⋅'⋅⋅⨯+='+'+'⋅'⋅⋅⨯+='+'+'⋅'⋅⋅⨯+=⋅⋅-⋅⋅=⋅⨯=⋅'''⋅===-2222222225)()()(21)()()(21)()()(21cos sin 103.704.022z y x z c F f z y x y c F f z y x x c F f k j w s rad S y x F c D rz D ryD rx D ρρρφωφωωμφC D is the angle of attack of a plane flew in the best state, w is the angular speed of a moving object, vector j and k are the unit vector on y and z direction respectively,μisrx F y w m x m -⋅'⋅⋅⨯=''φsin 2()ry F z x w m y m -'+⋅'⋅⨯-=''φφcos sin 2mg F y w m z m rz +-⋅'⋅⋅⋅=''φcos 2the coefficient of viscosity of the object.5.1.4 Solution of the ModelWhen air flows through an object, only the air close to layer on the surface of the ob-ject in the laminar airflow is larger, whose air viscosity performance is more noticea-ble while the outer region has negligible viscous force [8]. Typically, to simplify cal-culation, we ignore the viscous force produced by plane surface caused by air resis-tance.Step 1: the examination of dimension in modelTo verify the validity of the model based on Newton ‟s second theorem, first, we standardize them respectively, turn them into the standardization of dimensionless data to diminish the influence of dimensional data. The standard equation is:Step 2: the confirmation of initial conditionsIn a space coordinate origin based on plane, we assume the earth's rotation direc-tion for the x axis, the plane's flight heading as y axis, the vertical downward di-rection for z axis. Space coordinate system are as follows:Figure 1 Space coordinate systemStep 3: the simplification and solutionAfter twice integrations of the model, ignoring some of the dimensionless in thesxx y i -=integral process, we can simplify the model and get the following:⎪⎪⎪⎩⎪⎪⎪⎨⎧+'⋅⋅⋅-⋅'⋅⨯='''-⋅⋅⋅-⋅'⋅⨯-=''⋅'⋅⨯=''g z m s c y w z y v m s c z w y y w x D D 220)(2cos 2)(2cos 2sin 2ρφρφφWe can calculate the corresponding xyz by putting in specific data to get the in-formation about the point of losing contact.Step 4: the solution of the coordinateThe distance of every latitude on the same longitude is 111km and the distance ofevery longitude on the same latitude is 111*cos (the latitude of this point) (km). Moreover, the latitude distance of two points on the same longitude is r ×cos(a ×pi/180) and the longitude distance of two points on the same latitude is: r ×sin(a ×pi/180)[9].We assume a as the clockwise angle starting with the due north direction and r as the distance between two points; X 、Y are the latitude and longitude coordinates of the known point P respectively; Lon , Lat are the latitude and longitude coordi-nates of the unknown point B respectively.Therefore, the longitude and latitude coordinates of the unknown point Q is:⎪⎪⎩⎪⎪⎨⎧⨯⨯+=⨯⨯⨯⨯+=111)180/cos()180/cos(111)180/sin(pi a r Y Lat pi Y pi a r X LonThus, we can get coordinates of the point of splash by putting in specific data.5.2 Modeling For Locating WreckageIn order to understand how the wreckage distributes in the sea, we have to understand the whole process beginning from the plane crashing into water to reaching the seaf-loor. One intuition for modeling the problem is to think of the ocean currents as astochastic process decided by water velocity. Therefore, we use a differential equation method to simulate the impact on wreckage from ocean currents.A Bayesian Searching model is a continuous model that computing a probability dis-tribution on the location of the wreckage (search object) in the presence of uncertain-ties and conflicting information that require the use of subjective probabilities. The model requires an initial searching zone and a set of the posterior distribution given failure of the search to plan the next increment of search. As the search proceeds, the subjective estimates of the detection will be more reliable.5.2.1 Assumptions of the ModelThe following general assumptions are made based on common sense and weuse them throughout our model.●Seawater density keeps unchanged despite the seawater depth.Seawater density is determined by water temperature, pressure, salinity etc.These factors are decided by or affected by the seawater density. Considering the falling height, the density changes slightly. To simplify the calculation, we consider it as a constant.●The velocity of the wreck stay the same compared with velocity of theplane before it crashes into pieces. The whole process will end quickly witha little loss of energy. Thus, we simplify the calculation.●Marine life will not affect our simulation.Most open coast habitats arefound in the deep ocean beyond the edge of the continental shelf, while the falling height of the plane cannot hit.●Acting force of seawater is a function of the speed and direction of oceancurrents. Ocean currents is a complicated element affected by temperature, wide direction, weather pattern etc. we focus on a short term of open sea.Acting force of seawater will not take this factors into consideration.5.2.2 Preparation of the Model●The resistance of objects of different shapes is different. Due to the continuityof the movement of the water, when faced with the surface of different shapes, the water will be diverted, resulting in the loss of partial energy. Thus the pressure of the surface of objects is changed. Based on this, we first consider the general object, and then revise the corresponding coefficients.●Ocean currents and influencing factorsOcean currents, also called sea currents, are large-scale seawater movements which have relatively stable speed and direction. Only in the land along the coast, due to tides, terrain, the injection of river water, and other factors, the speed and direction of ocean currents changes.Figure 2Distribution of world ocean currentsIt can be known from Figure 2 that warm and cold currents exist in the area where aircraft incidences happened. Considering the fact that the speed of ocean currents slows down as the increase of the depth of ocean, the velocity with depth sea surface currents gradually slowed down, v x is set as the initial speed of ocean currents in subsequent calculations.●Turbulent layerTurbulent flow is one kind of state of the fluid. When the flow rate is very low, the fluid is separated into different layers, called laminar flow, which do not mix with each other. As the flow speed increases, the flow line of the fluid begins to appear wavy swing. And the swing frequency and amplitude in-creases as the flow rate increases. This kind of stream regimen is called tran-sition flow. When the flow rate becomes great, the flow line is no longer clear and many small whirlpools, called turbulence, appeared in the flow field.Under the influence of ocean currents, the flow speed of the fluid changes as the water depth changes gradually, the speed and direction of the fluid is un-certain, and the density of the fluid density changes, resulting in uneven flow distribution. This indirectly causes the change of drag coefficient, and the re-sistance of the fluid is calculated as follows:2fkvGLCM texture of submarine topographyIn order to describe the impact of submarine topography, we choose a rectan-gular region from 33°33…W, 5°01…N to 31°42‟W , 3°37‟N. As texture is formed by repetitive distribution of gray in the spatial position, there is a cer-tain gray relation between two pixels which are separated by a certain dis-tance, which is space correlation character of gray in images. GLCM is a common way to describe the texture by studying the space correlation cha-racter of gray. We use correlation function of GLCM texture in MATLAB:I=imread ('map.jpg'); imshow(I);We arbitrarily select a seabed images and import seabed images to get the coordinate of highlights as follows:Table 1Coordinate of highlightsNO. x/km y/km NO. x/km y/km NO. x/km y/km1 154.59 1.365 13 91.2 22.71 25 331.42 16.632 151.25 8.19 14 40.04 18.12 26 235.77 13.93 174.6 14.02 15 117.89 14.89 27 240.22 17.754 172.38 19.23 16 74.51 12.29 28 331.42 24.455 165.71 24.82 17 45.6 8.56 29 102.32 19.486 215.75 26.31 18 103.43 5.58 30 229.1 18.247 262.46 22.96 19 48.934 3.51 31 176.83 9.188 331.42 22.34 20 212.42 2.85 32 123.45 3.239 320.29 27.55 21 272.47 2.48 33 32.252 11.7910 272.47 27.55 22 325.85 6.45 34 31.14 27.811 107.88 28.79 23 230.21 7.32 35 226.88 16.0112 25.579 27.05 24 280.26 9.93 36 291.38 5.46Then we use HDVM algorithm to get the 3D image of submarine topography, which can be simulated by MATLAB.Figure 3 3D image of submarine topographyObjects force analysis under the condition of currentsf is the resistance, f i is the disturbance resistance, F f is the buoyancy, G isgravity of object.Figure 4Force analysis of object under the conditions of currentsConsidering the impact of currents on the sinking process of objects, wheninterfered with currents, objects will sheer because of uneven force. There-。
美国数学建模竞赛论文写作
2021/3/10
讲解:XX
14
三、写作规范
4. 写简单的句子
差:The value of the parameter a, which was used in the previous section to determine the height of the building, can also be used to determine its width. 好:In the previous section, we use the value of the parameter a to determine the height of the building. We can also use a to determine the width of the building.
国际数学建模竞赛 论文写作
参 考 书 目
2021/3/10
讲解:XX
2
说明:
※ 这不是灵丹妙药 ※ 这不是英语课程
2021/3/10
讲解:XX
3
一、写作的重要性 二、论文结构 三、写作规范 四、英语用法 五、符号与图标 六、数学表达式和句子
2021/3/10
讲解:XX
4
一、写作的重要性
1. 摘要是论文最重要的部分; 2. 写作是国际建模竞赛的难点.
差:We will now find the solutions of the following equation. 好:We will now solve the following equation.
2021/3/10
讲解:XX
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三、写作规范
8. 使用并列短语强调相似性
2021数学建模大赛获奖论文
2021数学建模大赛获奖论文眼科病床的合理安排摘要在医院里就医要排队,这是个非常普遍的问题。
对于医院来说,建立一个良好的排队等待接受服务的系统,对于保证医院秩序的正常是很有必要的。
问题一,我们选用了服务强度?、队长Ls、平均等待时间Wq和平均逗留时间Ws8.69=5.721.52>1,得出单位时间内离开系统的人数少于单位时间内到达的人数,因此,系统的人数会越来越多。
问题二,我们进行了数据的统计分析,得出病床安排规则如下表:星期入住病床安排规则(从左到右优先权依次降低)一,二外伤、白内障单眼、青光眼和视网膜疾病、白内障双眼三,四,五外伤、青光眼和视网膜疾病、白内障双眼、白内障单眼六,日外伤、白内障双眼、白内障单眼、青光眼和视网膜疾病四个指标来对当前病床安排模型进行评价,通过计算服务强度?=??=按照此规则得出结果,进行统计分析可得出此时的服务强度???<?=1.52,说明此优化模型比医院当前的病床安排规则FCFS好。
8.69?==1.117.85?问题三,根据问题二中模型的排队规则,对门诊病人进行入院时间、手术时间、出院时间进行预测,得出门诊病人的入住时间,可在其门诊时告知大致入住时间。
问题四,由于住院部周六日不安排手术,所以周四、周五的优先级别会发生如下改变,见下表:星期入住病床安排规则(从左到右优先权依次降低)一、二外伤、白内障单眼、青光眼和视网膜疾病、白内障双眼三外伤、青光眼和视网膜疾病、白内障双眼、白内障单眼四、五、六、日外伤、白内障双眼、白内障单眼、青光眼和视网膜疾病按照此规则,得出了医院手术新的时间安排。
问题五,将眼科门诊中可安排的病床首先安排外伤病人住院,然后按比例分配给其他几类病人,建立了非线性规划模型,用Matlab解出按比例分配模型下的平均最短逗留时间,为8.1953天。
关键词:排队论优先级排序法泊松分布优化模型1一、问题的背景医院就医排队是大家都非常熟悉的现象,它以这样或那样的形式出现在我们面前,例如,患者到门诊就诊、到收费处划价、到药房取药、到注射室打针、等待住院等,往往需要排队等待接受某种服务。
全国研究生数学建模竞赛三等奖 英文
全国研究生数学建模竞赛三等奖英文全文共6篇示例,供读者参考篇1Yay, I Won a Big Math Prize!Hi there, friends! Guess what? I have some super exciting news to share with you all! You know how much I love math, right? Well, my love for numbers and solving tricky problems just paid off in a huge way!A little while ago, I entered this really cool contest called the National Postgraduate Mathematical Modeling Contest. It's a big deal, and lots of smart grown-ups who are studying to get their master's degrees or PhDs take part in it. At first, I wasn't sure if I should even try because, you know, I'm just a kid, and those other people are way older and probably know a lot more about math than I do.But my mom always tells me that if I work hard and believe in myself, I can achieve great things. So, I decided to give it a shot! And boy, am I glad I did!The contest was all about using math to solve real-world problems. They gave us this really tricky situation involving traffic patterns, resource management, and all sorts of complicated stuff. I won't bore you with all the details, but let's just say it was a doozy!For days, I pored over the problem, scribbling equations, and drawing diagrams all over my bedroom walls (sorry, Mom!). I even had to learn some new mathematical concepts that I'd never heard of before. But you know what? I didn't give up! I kept pushing forward, determined to crack the code.And you know what happened? After countless hours of hard work and more than a few late nights, I finally figured it out!I came up with a solution that not only made sense but also addressed all the different aspects of the problem. I was so proud of myself!When the results came in, and they announced that I had won the Third Prize in the whole contest, I couldn't believe it! I was jumping up and down, squealing with joy, and doing my happy dance all around the house. My parents were so proud of me, and my little sister even gave me a big, slobbery kiss on the cheek (yuck!).But you know what the best part was? Not the shiny medal or the fancy certificate (although those were pretty cool too!). The best part was knowing that all my hard work and perseverance had paid off. I had proven to myself that even though I'm just a kid, I can still achieve amazing things if I put my mind to it.So,篇2Yay, I Won a Big Math Prize!Hi friends! I have some super exciting news to share with you all. You know how I've been spending a lot of time lately working on math problems and entering math competitions? Well, it paid off in a really big way! I entered the National Graduate Mathematical Modeling Competition and my team won third place! Can you believe it? Little old me, winning such an important prize. I'm still pinching myself to make sure it's real!The competition was no joke, let me tell you. Hundreds of really smart university students from all across the country took part. We had to solve these really tricky math problems and create models to represent real-world situations. It took a lot ofhard work, brain power, and definitely a few all-nighters! But my teammates and I put our heads together and didn't give up.I'll give you an example of one of the problems we had to tackle. They asked us to look at traffic patterns in a big city and figure out the best way to reduce congestion during rush hours. We had to take into account things like the number of cars on the road, the timing of traffic lights, potential public transit solutions, and more. It made my head spin at first! But we broke it down step-by-step and used our math skills to build a model that could analyze different scenarios.In the end, our model showed that by adjusting the timing of some traffic lights and adding a few extra bus routes, the city could reduce rush hour traffic by 18%! We put together a big report explaining our approach and submitted it to the judges. Crossing our fingers paid off when they awarded us third place out of all the entries nationwide. A huge achievement!Another problem was about figuring out the most efficient way for a brand new package delivery service to serve customers in a particular region. With math, we could map out the shortest routes, determine ideal locations for distribution hubs, and ensure fast delivery times. Who knew math could be so useful for getting your holiday presents on time?Solving these challenges was like cracking a super tricky code. My brain definitely got a work-out! But it was so rewarding and fun to apply everything I've been learning in school to real situations. I have such a deep appreciation now for how important math and modeling are in running businesses, cities, transportation, and more. Math makes the world go round!My teammates were amazing too. At first, we had some disagreements and frustrations when we couldn't figure things out. But we learned to be patient, listen to each other's ideas, and combine our strengths. Having teammates good at coding helped us build computer programs to test our models. The few older students mentored me and my friends when we got stuck. Teamwork and perseverance were just as important as math skills!When they announced the winners at the big ceremony, we screamed so loud! My parents were in the audience cheering us on and giving us big hugs after. I've never felt so proud and accomplished. All that late-night studying, handling setbacks, writing and re-writing our reports...it was worth every second to hear our names called!Winning third place means we get some prize money, which is awesome. But even better is the confidence and determinationit gave me to keep exploring the amazing world of mathematics.I know I can take on any challenge and use my problem-solving skills to make a difference, just like we did in this competition.Who knows, maybe I'll become a trailblazing mathematician or scientist when I grow up and make the next big breakthrough! Math is So cool and this competition made me love it even more. Just watch out world, the math ninja is coming for you!For any of my friends thinking about entering math competitions, I say go for it! You'll learn so much, make new friends, and get to flex your brain muscles in the best way. If a kid like me can take third place in a huge national contest, just imagine what you can achieve. The possibilities are infinite when you put your mind to it! Let's make math awesome together.篇3Yay! We Won a Big Math Prize!Hi there! My name is Timmy and I'm going to tell you all about the super cool math contest that my friends and I entered. It was called the National Postgraduate Mathematical Modeling Contest, which is a really big deal! Grown-ups from all over the country take part in it.Now, I know what you're thinking - math, yuck! But trust me, this competition was actually a lot of fun. It wasn't just about solving boring equations on a chalkboard. We got to use math to solve real-world problems, kind of like being a detective or a puzzle master!Our team was made up of me, my best friend Johnny, and our super smart classmate Susie. We had to work together, putting our heads together to crack these tricky math cases. It was like being part of a secret math club!The first round was all about coming up with a plan to reorganize a city's trash collection system to make it more efficient. We had to think about things like the number of trucks needed, the best routes for them to take, and how to minimize fuel costs. Using our math skills, we mapped out the perfect strategy!Next up was a challenge involving scheduling flights for an airline. We had to figure out the optimal flight times, routes, and even how many planes the airline should have. It was like being tiny air traffic controllers, but without the fancy headsets!For the final round, we tackled a super tough problem about managing water resources in a region. We looked at things like rainfall patterns, population growth, and agricultural needs tocome up with a plan for ensuring everyone had enough water. Solving that one made me feel like a real environmental superhero!After all that hard work, you can imagine how excited we were when we found out we had won third place! We got to go up on a big stage and receive our prize - a shiny trophy and some cool math books. My parents were so proud of us, they took us out for pizza to celebrate.Even though the contest was really challenging, it just goes to show that math can be fun and useful for solving all sorts of interesting problems in the real world. Who knows, maybe one day you'll be a math modeling master too!So that's the story of how my friends and I became math contest champions. We used our brains, worked as a team, and had a blast doing it. Math rocks!篇4Yay! I Won Third Place in the Big Math Modeling Contest!Hi everyone! I'm so excited, I can hardly sit still to tell you my big news. A few months ago, I entered this huge math competition called the National Graduate MathematicsModeling Competition. It was really, really hard and I had to work super duper hard, but guess what? I won third place! Can you believe it?I'll tell you all about how it happened. It started when my math teacher, Mrs. Garcia, told our class that we could enter this contest if we wanted to. She said it would be really challenging and we'd have to work together as a team to solve these massive math problems. At first, I wasn't sure if I wanted to do it because it sounded so difficult. But then she said the winners would get prizes and awards, and I really like winning prizes!So I decided to enter the contest along with three of my best friends - Tommy, Jamal, and Sophia. We made a great team because we all loved math and were ready to work really, really hard. The first step was just signing up and letting the contest organizers know we wanted to compete.A few weeks later, we got an email with the math problem we had to solve. It was suuuuper long and confusing with tons of numbers, graphs, and equations. I thought my brain was going to melt just looking at it! But we didn't give up.We had 72 hours to work on the problem and turn in our solution. That's three whole days and nights! So we got together at my house and started working. We made snack breaks to eatpizza and drink lots of juice to keep our brains working. We took nap breaks too when we got sleepy.It was like a math sleepover party, but without the pillow fights! We used all kinds of math skills - algebra, calculus, geometry, statistics, and more. We drew diagrams on the windows with dry erase markers. We made charts and graphs. We built models with blocks and Legos. Anything to try to understand and solve the humongous problem.With just a few hours left before the deadline, we were stumped. None of our solutions seemed to be working. We thought we might have to give up. But then, Jamal had a brilliant idea that helped us finally crack the code! We worked fast and furiously to write up our final answer and submit it with just 15 minutes to spare. Phew!A couple months went by and we had almost forgotten about the contest. Then one day, an envelope arrived in the mail addressed to our team. We ripped it open and there was a certificate inside saying we had won third place in the whole national competition! We couldn't believe it. We jumped up and down screaming and cheering.As our prize, we each got a brand new tablet computer and a special medal. My medal says "National Graduate MathematicsModeling Competition Third Place" on it. I'm so proud, I never take it off. I wear it to school, to bed, even in the bathtub!Some of the other prizes were even bigger. The first place team won an all-expenses paid trip to Florida to visit NASA. And the second place team got to meet a famous mathematician in person. Maybe next year we'll try to win one of those!This experience showed me that even though math can be super hard, if you work together as a team and never give up, you can accomplish amazing things. Winning third place in such a huge, difficult competition feels just awesome. I hope we can enter again next year and maybe even get first! Who's with me?篇5The Awesome Math AdventureHello, my friends! I'm so excited to share with you an amazing adventure I had recently. It was all about using math in a really fun and challenging way!You know how some grown-ups think math is just about numbers and equations? Well, let me tell you, it's so much more than that! Math can help us explore the world around us, solve real-life problems, and even have a ton of fun while doing it.A few months ago, my teacher told our class about this really cool competition called the National Postgraduate Mathematical Modeling Contest. At first, I wasn't sure what it was all about, but as soon as she explained it, I knew I wanted to be a part of it!You see, in this contest, teams of students get to work together to solve a real-world problem using math. It's like being a detective or an explorer, but instead of looking for clues or hidden treasures, we use numbers, equations, and our brilliant minds to find solutions.Our team was made up of three members: me, my best friend Emily, and our classmate Alex. We were all super excited and a little nervous, but we knew that with our combined math skills and teamwork, we could do something amazing.The problem we had to solve was all about helping a company figure out the best way to distribute their products to different cities. It might sound a bit boring at first, but let me tell you, it was anything but boring!We had to consider all sorts of factors, like the distance between cities, the cost of transportation, the demand for the products in each city, and even things like traffic and weather conditions. It was like putting together a giant puzzle, but instead of pieces, we had equations and data to work with.At first, it was a bit overwhelming. We had to gather all the information we needed, organize it, and then start building our mathematical model. But as we worked together, sharing ideas and helping each other out, it all started to make sense.Emily was a whiz at organizing the data and making sure we didn't miss anything important. Alex was great at coming up with creative ways to approach the problem, and I was the one who loved putting all the pieces together and checking our work.We spent countless hours working on our model, writing code, and running simulations. There were times when we felt stuck or frustrated, but we never gave up. We kept encouraging each other, taking breaks when we needed to, and coming back to the problem with fresh minds.Finally, after weeks of hard work, we had our solution ready. We double-checked everything, made sure our presentation was clear and easy to understand, and then it was time to submit our entry.Waiting for the results was the hardest part. We knew we had given it our all, but there were so many other talented teams competing. When the announcement came that we had won the Third Prize, we were over the moon!All our hard work and determination had paid off, and we couldn't have been prouder of ourselves. We had proven that kids like us could take on a real-world challenge and come up with amazing solutions using math.But you know what the best part was? It wasn't just about winning a prize. It was about the journey we went through together, the skills we learned, and the confidence we gained in our abilities.We learned that math isn't just about numbers and formulas in a textbook. It's a powerful tool that can help us understand the world around us and make it a better place. We learned how to work as a team, communicate effectively, and never give up, even when things got tough.So, my friends, if you ever get the chance to participate in a math competition or tackle a real-world problem using math, don't hesitate! It might seem scary at first, but trust me, it's an adventure you'll never forget.And who knows, maybe one day you'll be writing your own story about winning an award for your brilliant math skills and teamwork. Just remember to have fun, work together, and always believe in yourselves!篇6Certainly! Here's an article about winning the Third Prize in the National Graduate Mathematical Modeling Contest, written in English from a primary school student's perspective, with a length of approximately 1000 words.Yay, I Won a Math Prize!Hi, my name is Timmy, and I'm a third-grader. I know what you're thinking, "How can a kid like you win a math prize?" Well, let me tell you all about my super cool adventure!Last month, my teacher, Ms. Johnson, told us about this thing called the National Graduate Mathematical Modeling Contest. It sounded like a bunch of big, fancy words to me, but she said it was a really important math competition forgrown-ups. I thought to myself, "Math? That's my favorite subject! I love solving puzzles and playing with numbers."So, I decided to give it a shot. My parents were a bit surprised when I told them I wanted to enter a graduate-level math contest, but they've always encouraged me to follow my dreams. After a lot of begging and puppy dog eyes, they finally agreed to let me try.The first step was to pick a team. I asked my best friends, Tommy and Susie, if they wanted to join me. They're both super smart too, and we make an awesome team. We spent weeks working on our project, staying up late, and drinking lots of chocolate milk (because what's a math competition without chocolate milk?).The day of the contest finally arrived, and we were all nervous but excited. We walked into this huge auditorium filled with people who looked like they had PhDs and stuff. Everyone was staring at us like we were aliens or something. But we didn't let that stop us!When they announced the problem, it was about something called "supply chain optimization." It sounded complicated, but we broke it down into smaller pieces and attacked it one step at a time. We used our knowledge of algebra, geometry, and even a little bit of coding to come up with a solution.After hours of hard work, we finally submitted our project. We were exhausted but proud of what we had accomplished. A few weeks later, the results came in, and we couldn't believe our eyes – we had won the Third Prize! We were the youngest team to ever place in the competition.The awards ceremony was a blast. We got to stand on a big stage and receive our trophy and certificates. Everyone was clapping and cheering for us. It was like we were rock stars or something!But the best part was seeing the look of pride on our parents' faces. They knew how hard we had worked and how much this meant to us. We proved that age is just a number and that with determination and teamwork, anything is possible.So, there you have it, folks – the story of how three ordinary kids took on a graduate-level math competition and came out on top. Who knows, maybe next year we'll go for the first prize!。
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Water, Water, EverywhereSummaryDue to population growth, economic development, rapid urbanization, large-scale industrialization and environmental concerns water stress has emerged as a real threat. [1]This paper was motivated by the increasing awareness of the need for fresh water since fresh water crisis is already evident in many areas on the world, varying in scale and intensity.Firstly, we testify water demand and supply sequence are stable by means of unit root test, then predict the freshwater demand and supply in 2025 by using ARMA Model and Malthus Population Model .Secondly, we give more concern on four aspects: Diversion Project, Desalinization, Sewage treatment and Conservation of water resources, building some models such as Cost-benefits analysis and Tiered water pricing model. Comparing the cost-benefit ratio, the sewage treatment cost-benefitratio is the smallest--0.142, that is to say it is more cost-efficient.Finally, we use our models to analyze the impacts of these strategies, we can conclude that conservation of water resources is the most feasible.Keywords:Cost-benefit analysis ARMA ModelTiered water pricing modelA Letter to a governmental leadershipFebruary 4, 2013Dear Sir,During the four days working, our team spares no effort using cost and benefits analysis determine water strategy for 2013 about how to use water efficiently to meet the need in 2025. Now, we outline our conclusion to you.z Diversion ProjectThe South-North Water Transfer Project is a multi-decade infrastructure project solved the unbalance of water resource. The cost is 6.2yuan/3m, and it will much higher while the distance is more than 40 kilometers.z DesalinizationDesalinization utilizes the enormous seawater and provides freshwater in a cheaper price. However, interior regions with water scarcity can hardly benefit from it as most desalinization manufacturers located on eastern coastal areas. The cost of production is 5.446 yuan/t, but the transport costs less the cost-efficient competitiveness. The cost can be decreased by using more advanced technology.z Sewage treatmentSewage treatment can relief the environmental impact of water pollution by removing contaminants from water, the cost of Sewage treatment is 0.5yuan/t. z Conservation of water resourcesConservation makes sure of the source of rational use of water. There are several approaches on water resources conservation, the main problem is the lack of supervision. The benefit-cost ratio is between 0.95 and 3.23, and it has a high return-investment ratio.z Each of the above water strategy has its own advantages and disadvantages, we should consider the aspects of economic, physical, environmental, geographical, and technique factors overall, then choose the optimal strategy for different area.Yours sincerely,COMAP #23052ContentI Introduction (2)II Assumptions (3)III Models (3)3.1 The prediction of freshwater shortage in 2025 (3)3.1.1 The prediction of freshwater demand (3)3.1.1.1 The description of basic model (3)3.1.1.2 Model building (4)3.1.1.3 Model prediction (5)3.1.2 The prediction of freshwater supply (7)3.1.2.1 Model building (7)3.1.2.2 Model prediction (8)3.1.3. Conclusion (9)3.2Water strategy (9)3.2.1 Diversion Project (9)3.2.2 Desalinization (14)3.2.3 Sewage Treatment (16)3.2.4 Conservation of water resources (19)3.2.4.1 Agricultural water saving (20)3.2.4.2 Life water saving (21)IV The influence of our strategy (25)4.1 The influence of Water Diversion Project (25)4.2 The influence of desalination (25)4.3 The influence of sewage treatment (26)4.4 Water-saving society construction (26)V References (27)VI Appendix (28)I IntroductionAccording to relevant data shows that 99 percent of all water on earth is unusable, which is located in oceans, glaciers, atmospheric water and other saline water. And even of the remaining fraction of 1 percent, much of that is not available for our uses. For a detailed explanation, the following bar charts show the distribution of Earth's water: The left-side bar shows where the water on Earth exists; about 97 percent of all water is in the oceans. The middle bar shows the distribution of that 3 percent of all Earth's water that is fresh water. The majority, about 69 percent, is locked up in glaciers and icecaps, mainly in Greenland and Antarctica.[2] Except for the deep groundwater which is difficult to extract, what can be really used in our daily life is just 0.26 percent of all water on earth.Figure 1 The distribution of Earth's waterFreshwater is an important natural resource necessary for the survival of all ecosystems. There is a variety of unexpected consequence due to the lack of freshwater: 6,000 children die every day from diseases associated with unsafe water and poor sanitation and hygiene; Unsafe water and sanitation leads to 80% of all the diseases in the developing world;[3]Species which live in freshwater may be extinct, thus, breaking the food chain balance severely; The development of economic slow down in no small measure.It is with these thoughts in mind, many people think freshwater is very important than ever before.So, how to use freshwater efficiently? What is the best water strategy? Readmore and you will find more.II AssumptionsIn order to streamline our model we have made several key assumptions :1. We chose China as the object study.2. The water consumption of the whole nation could be approximate regardedas the demand of water .3. The Precipitation is in accordance with the supply of water .4. No considering about sea level rising because of global warmingIII Models3.1 The prediction of freshwater shortage in 2025How much freshwater should our strategy supply? Firstly, our work is to predict the gap between freshwater demand and supply in 2025. We obtain thefreshwater consumption data from China Statistical Yearbook. 3.1.1 The prediction of freshwater demandWe forecast the per capita demand for freshwater by building the ARMA Model .3.1.1.1 The description of basic modelThe notation ARMA(p, q) refers to the model with p autoregressive termsand q moving-average terms. This model contains the AR(p) and MA(q) models,mathematical formula is:qt q t t t p t p t t t y y y y −−−−−−−−−−+++=εθεθεθεφφφ......22112211 (1) AR(p) modelt p t p t t t y y y y εφφφ+++=−−−...2211 (2) MA(q) model q t q t t t t y −−−−−−−=εθεθεθε....2211 (3)),.....,2,1(p i i =φ ,),.....,2,1(q j j =θare undetermined coefficients of themodel, t ε is error term, t y is a stationary time series.3.1.1.2 Model buildingAll steps achieved by using EviewsStep1: ADF test stability of sequenceNull hypothesis:1:0=ρH , 1:1≠ρH , ρis unit root.Table 1 Null Hypothesis: Y has a unit root Exogenous: Constant Lag Length: 3 (Automatic based on SIC, MAXLAG=3) t-Statistic Prob. Augmented Dickey-Fuller test statistic -5.3783580.0040 Test critical values: 1% level-4.582648 5% level -3.32096910% level -2.801384We know Prob=0.0040 that we can reject the null hypothesis, and thenydoesn’t have a unit root, in other words, is stationary series. Step 2: Building the ARMA ModelThen we try to make sure of p and q by using the stationary series y .Table 2Date: 02/02/13 Time: 11:08Sample(adjusted): 2001 2011Included observations: 11 after adjusting endpointsConvergence achieved after 12 iterationsBackcast: 1998 2000Variable Coefficie nt Std. Error t-StatisticProb.AR(1) 1.0105040.005813173.8325 0.0000MA(3) 0.9454040.03650725.89639 0.0000R-squared 0.831422 Mean dependent varAdjustedR-squared 0.812692 S.D. dependent varS.E. of regression 5.085256 Akaike info criterionSo, we can get the final model, is:310.9454041.010504−−+=t t t d y y ε (4)3.1.1.3 Model predictionStep 1: The prediction of per capita freshwater demandWe use model (4) to predict the per capita demand of freshwater in the year2025, the result as Figure3.Figure 2 sequence diagram of dynamic predictionFrom the diagram, we can see the per capita freshwater demand is raising.The detailed data as Table3: Table 3 2010 2011 2012 2013 2014 2015 2016 2017 483.3584 488.4357 493.5662 498.7507503.9896509.2836514.6332 520.03892018 2019 2020 2021 2022 2023 2024 2025 525.5015 531.0214 536.5993 542.2358547.9315553.6871559.503 565.3801(cu.m/person)Through the above efforts, we get the 2025 per capita freshwater demand is565.3801 cu.mStep 2: The prediction of the whole freshwater demandThe relationship among d Q ,t N ,daverage Q is: daverage t d Q N Q ×= (5)d Q is the whole demand of freshwater, t N is the total population ,daverage Q is per capita of freshwater demand.Then we etimate the total population by the Malthus Population Model . rt e N t N 0)(=[4] (6))(t N is the population at time t,0N is the population at time 0,r is net relative growth rate of the populationrt e N N 2011)2025(= (7)By calculating, we get:(billion)42.11.347)2025(1500479.0≈=×e N (8)At last,we could get the whole demand of freshwater while the time is 2025.38.5652.14)2025(×=×=daverage d Q N Q ()cu.m million 100 8028.396= (9)3.1.2 The prediction of freshwater supplySimilarily,we predict freshwater supply using the ARMA Model. 3.1.2.1 Model buildingStep1: ADF test stability of sequenceNull hypothesis:1:0=ρH , 1:1≠ρH , ρis unit root. Table 4 Null Hypothesis: D(Y) has a unit root Exogenous: Constant Lag Length: 2 (Automatic based on SIC, MAXLAG=3)t-Statistic Prob. Augmented Dickey-Fuller test statistic-9.433708 0.0002 Test critical values: 1% level -4.803492 5% level -3.40331310% level -2.841819From the table, we find that first difference of supply data is smooth, we canreject the null hypothesis, that is ()y D is a smooth series.Step 2: Building the ARMA ModelWe use the smooth series ()y D to make sure the number of order.Table 5Date: 02/02/13 Time: 14:16Sample(adjusted): 2002 2010 Backcast: 1999 2001Variable CoefficientStd. Error t-Statistic Prob. AR(1) 0.6351030.158269 4.012804 0.0051 MA(3) -0.9923370.069186-14.34306 0.0000 R-squared 0.812690 Mean dependent var 50.51111Adjusted R-squared 0.785931 S.D. dependent var 119.1793S.E. of regression 55.14139 Akaike info criterion 11.05081Sum squared resid 21284.01 Schwarz criterion11.09464 Log likelihood -47.72864 Durbin-Watson stat 2.895553Then ,we get the final model is:)0.992337D(-)0.635103D()(31−−=t t t s y y D ε (10) 3.1.2.2 Model predictionWe use the effective model to predict freshwater supply in short-term until theyear 2025.Figure 3 sequence diagram of dynamic predictionFrom the diagram, we can see the supply remains unchanged basically .T The detailed data as Table6: Table 6 2010 2011 2012 2013 2014 2015 2016 2017 5630.203 5630.594 5630.843 5631.0015631.1025631.1655631.206 5631.2322018 2019 2020 2021 2022 2023 2024 2025 5631.248 5631.258 5631.265 5631.2695631.2725631.2735631.275 5631.275(100 million cu.m)According to the above data,we gain the supply of freshwater 2025, is5631.275(100 million cu.m)3.1.3. ConclusionFrom the above result,we find a serious issue:Table 7Year Demand offreshwater Supply of freshwater Net demand Unit2025 8028.396 5631.275 2397.121(100 million cu.m)In the year 2025, China will face the serious situation of freshwater shortage, the gap will reach 2397.121(100 million cu.m), therefore, in order to avoid this, we need to determine a series strategy to utilize freshwater efficiently.3.2Water strategy3.2.1 Diversion ProjectOn one hand, in view of Figure4, we can get information: Southeast coast is of the maximum precipitation, followed by the northern region, the western least.Figure 4 Precipitation Allocation Map of Major CitiesOn the other hand, in view of Figure 5, we can get information: The northern region and the southern coastal areas have the most water consumption, the western use less.Figure 5 Water Use MapDetailed data see to attached Table8 and Table9.South-to-North Water Diversion ProjectThe South–North Water Transfer Project is a multi-decade infrastructure project of China to better utilize water resources. This is because heavily industrialized Northern China has a much lower rainfall and its rivers are running dry. The project includes a Eastern, a Central and a Western route.Figure 6 The route of South-to-North Water Diversion ProjectHere, we take Western Route Project (WRP) as a representative, analysis the cost and benefits. As the strategic project to solve the problem of poorer water Northwest and North China, WRP will divert water from the upper reach of Yangtze River into Yellow Rive.Cost and benefits analysisThe direct quantitative economic benefits include urban water supply economic benefits, ecological environment water supply economic benefits, and the Yellow River mainstream hydroelectric economic benefits.[5]Urban water supply economic benefits:(1) Calculation MethodIn view of the water shadow price is difficult to determine, the equivalent engineering is not easy to choose, and the lack of water loss index is unpredictable, combined with the stage job characteristics, we select the method of sharing coefficient to calculate the urban water supply economic benefits.(2) Calculation ParametersThe Water consumption quota of per ten thousand yuan industrial output value is based on status quota, the predicted water consumption quota of per ten thousand yuan output value according to reach in 2 0 2 0 is :Lanzhou tom/ ten thousand yuan, gantry to Sanmenxia HeKouZhen river section for 26 3m/ ten thousand yuan. After a comprehensive analysis, set the reach for 20 3industrial water supply benefit allocation coefficient values 2.0 %.(3) Calculation ResultsAccording to (1) and (2), get table 10:Table 10water supply 3.2 billion 3.mproject benefits 20 billion yuan.8yuan /3maverage economic benefit 70z Ecological environment water supply economic benefits:(1) Calculation methodTake Forestry and animal husbandry as the representative, calculate whoseirrigation Economic benefits, and consider the allocation function of water supply. Analyse forestry benefits in reference with the increased wood savings, Animal husbandry in reference with the increased output of animals which were feeded by the incresed irrigation pasture (represented by sheep), both Forestry and animal husbandry account for half of the Ecological environment water supply.(2) Calculation parameters Set the water consumption quotas of Forestry irrigation unified as 233750hm m , the water supply sharing coefficient of Xiang irrigation as 0.60. In the calculation of forestry benefit, the increase of accumulated timber amount is ()a hm m ⋅235.22, timber price is 3300m yuan ; in the calculation of animal husbandry benefit , the increased stocking rates of unit pasture area is 25.22hm , taken a standard sheep price as yuan 260.(3) Calculation ResultsAccording to (1) and (2), the ecological environment water supply economic benefits is 714.1 billion, in which, The Yellow River replenishment economic benefits is 008.1billion yuan.z Hydroelectric economic benefits.(1) Diversion increased energy indicators:The increased electricity indicators is 306.9billion h kw ⋅, capacity enlargement the scale of 241 ten thousand kw .(2) Calculation methodTake the Optimal equivalent alternative engineering cost method, chosen fire electricity as an alternative project which can meet the power requirements of grid electricity equally. The sum of alternative engineering required annualinvestment translation and the annual running costs is increased annual power generating efficiency of the Yellow River cascade hydropower stations. (3) Calculation parametersThe power plant construction investment of kw $450, duration of five years, the investment proportion were 10%, 25%, 35%, 25%, 5%. Both the economic life of mechanical and electrical equipment and the metal structures equipment are taken as 20 years, considering the update ratio as 80% of the original investment. Standard coal price is taken as 160 dollars, standard coal consumption is taken as ()h kw g ⋅350. The fixed run rates take 4.5%, thesocial discount rate is 12%, the hydropower economic useful life of 5 years.(4) Calculation ResultsBy analysis and calculation, the first phase of water regulation produce the hydropower economic benefit is 3.087 billion.z Total economic benefits:Preliminary cost estimates of the project diversionOn the basis of economic nature classification, the total cost includes themachinery depreciation charges, wages and welfare costs, repair costs, thecost of materials,water district maintenance fees, management fees, water fees, interest expense and other . Analysis in the light of various estimates condition, the cost of water diverted into the Yellow River is 31~7.0m yuan c =The cost-benefit rate ()85.8~2.61∈=rc ω (11) 3.2.2 DesalinizationThough diversion project can balance water supply between places one has enough water and the other has water shortage, the costs will higher than desalinization when the distance more than 40 kilometers.Desalinization and comprehensive utilization of the work are increasingly taking centre stage on the problem of solving freshwater scarcity. Many countries and areas devote to optimize an effective way by enhancing the development of science and technology.According to the International Desalination Association, in 2009,14,451 desalination plants operated worldwide, producing 59.9 million cubic meters per day, a year-on-year increase of 12.3%.[6] The production was 68 million 3m in 2010, and expected to reach 120million 3m by 2020; some 40 million 3m is planned for the Middle East.[7]China has built more than 70 sets of sea water desalinization device with the design capacity of 600,000m3 and an average annual growth rate of more than 60%; technology with independent intellectual property rights of a breakthrough in the reverse osmosis seawater membranes, high pressure pumps, devices for energy recovery achieved significant progress, the desalinization rate raises from 99.2% to 99.7%; conditions of industrial development and the desalination market has been basically formed.MethodsDe-salinization refers to any of several processes that remove some amount of salt and other minerals from saline water. More generally, desalination may also refer to the removal of salts and minerals.[8] Most of the modern interest in desalination is focused on developing cost-effective ways of providing fresh water for human use.There are two main methods of desalinization:1. Extract freshwater from saline water: Distillation (Multi-stage flash distillation, Vapor compression distillation, Low temperature multi-effect distillation), Reverse osmosis, Hydrate formation process, Solvent extraction, Freezing.2. Remove salt from saline water: Ion exchange process, Pressure infiltration method, Electroosmosis demolition method.For desalination, energy consumption directly determines the level of the cost of the key. Among the above methods, reverse osmosis is more cost-effective than the other ways of providing fresh water for human use. So, reverse osmosis technology has become the dominant technology in international desalinization of seawater.The following two figures show the working principle diagram of a reverse osmosis system.Figure7 working principle diagram of a reverse osmosis systemCost and benefits analysisTable 12 general costs for a reverse osmosis systemItem Unitprice(yuan/t)Chemicals cost 0.391electric charge 2.85Wages 0.034 Labor costWelfare 0.04 Administrative expenses 0.0008maintenance costs 0.23Membrane replacement cost 0.923Depreciationexpense Fixed assets depreciation0.97expenseTotal costs 5.446Table 13 general benefit for a reverse osmosis systemItem ValueHourly output(t) 10Working hours/day24 Daily output(t)240 Working days/year 365 Yearly output(t)87600 Yearly other benefits(yuan)310980 Unit water other benefits3.55 Water Price(yuan/t)8 Unit water total benefits11.55 Unit water total benefit 55.11=rWater cost-benefit ratio 4715.055.11446.52===r c w (12) 3.2.3 Sewage TreatmentSewage treatment is an important process of water pollution treatment. It uses physical, chemical, and biological ways removing contaminants from water . Its objective is to relief the environment impact of water pollution.This diagram shows a typical sewage treatment process.Figure 8 Sewage treatment flow mapTake Sewage Treatment Plant in east china as an example to analysis the cost and benefit of sewage treatment.Suppose:Sewage treatment scale d t x 100001=,The Sewage Treatment Plant workdays in a year 300=d ,Concession period is twenty to thirty years, generally 251=t years, Construction period is one to three years, generally 32=t years.Operation period = Concession period - Construction period.Cost estimation Table 14 fixed investment estimate c1(ten thousand Yuan)number project ConstructioninvestmentEquipment investment 1 Preprocessing stage38 27 2Biological treatment section 42 134 3End-product stage 11 44 4 Sludge treatment section 6323 5 accessory equipment 456 Line instrument 687 Construction investment 3008 Unexpected expense 809 Other expense 10010 Total investment975 Table 15 Operating expense estimate c2 (ten thousand Yuan)[9]number project expenses1 maintenance expenses 6.52 wages 103 Power Consumption 404Agent cost 10 5 Small meter operating cost 66.56 Amortization of intangibles 127Amortization of Construction 6.6 8Amortization of Equipment 19.8 9Annual total cost 104.9 10 Tons of water operation cost 0.29Annual total investment 15022213=+÷=c c c ten thousand YuanAnnual amount of sewage treatment t x x 3000000100003003001=×=×= Unit sewage investment t yuan t yuan x c c 5.03000000150000034=÷=÷= Benefit analysisSewage mainly comes from domestic sewage(40%), industrial sewage(30%), and the others(including stormwater , 30%)Sewage treatment price: domestic sewage is about t yuan 8.0, industrialsewage is about t yuan 5.1, and other is about t yuan 5.2.Unit sewage treatment approximate price t yuan t yuan t yuan tyuan p 52.1%302%305.1%408.01=×+×+×=Unit Sewage treatment benefit:t yuan p p r 52.321=+= Cost-benefit ratio 142.052.35.043===r c ω (13) 3.2.4 Conservation of water resourcesTo realize the sustainable development of water resources, one of the important aspects is the conservation of water resources. Saving water is thekey of conservation, so, we the construction of water-saving society is the keyof water resources conservation strategy.To construct the water-saving society, we give more concern about two aspects:agricultural water saving and life water saving. Finally, we analysis the cost andbenefit about water-saving society by building model.3.2.4.1 Agricultural water savingStrategic suggestions of water-saving agriculture1. Strengthen the government policies and public finance support2. Mobilizing all social forces to promote water-saving agriculture development3. Innovating enterprises to improve the science and technology4. Suggesting countries to regard water saving as a basic state policy5. Implement the strategy of science and technology innovationwater saving function product research and development as the key point, the research and development of a batch of suitable for high efficiency and low energy consumption, low investment, multi-function water saving and high efficient agriculture key technology and major equipment. Micro sprinkler irrigation water saving technology and equipment is the typical technology.[10] Typical analysis: drip irrigation technologyIrrigation uniformity DU and field irrigation water utilization αE can be expressed as the technical elements of the function :[11]),,,,,,(01co c in t F I S n L q f DU α=),,,,,,,(0SMD t F I S n L q f E co c in αα=RD SMD fc )(θθ−=in q is single discharge into earth,L is (channel) long,n is manning coefficient,0S is tiny terrain conditions,c I is soil infiltration parameters,αF is (channel) cross-sectional parameters,co t is irrigation water supply time,SMD is irrigation soil water deficit value,fc θ is the soil field capacity,θis the soil moisture content,RD is the root zone depth.According to the study we found that the use of modern surface irrigation technology such as sprinkler irrigation, micro spray irrigation and pressure irrigation system, can improve the utilization rate of water to 95%, better than common ground water saving irrigation mode, more than 1/2 ~ 2/3 of water-saving irrigation mode, therefore, advanced water saving technology is very important. 3.2.4.2 Life water saving China is a country with a large population and scarce water , so we should use water more reasonably and effectively.Tiered water pricing modelThe model is for all types of users in certain period to regulate basic water consumption, in the basic consumption, we collect fees by the basic price standard, when actual consumption beyond basic consumption, the beyond part will introduce penalty factor: the more water exceed, the higher punishment rate will be. For actual consumption is less than basic consumption, the user can get additional incentives, encouraging people to save water .[12] Three ladder water price modelWe assume that urban resident’s basic water consumption is 1q , the first stage water price is 1P , the second stage water price is 2P , by analogy, q P is used to express the water price in stage q , model formula is()()⎪⎪⎩⎪⎪⎨⎧−++−+−+=−)(11211121111m m q q q p q q p q p q q p q p q p p L L L (14) From the equation (14), that in the tiered water pricing system, as more price levers are divided, it will be more able to reflect the city water supply’s public property and public welfare, be much beneficial to motive users to save water . On the other hand, much more price levers will be bound to increase the transaction cost of both the water supplier and the water user . Seeing from practical application effects of the current step water price model , Three ladder water price model much meets the actual functional requirements of urban water supply system in our country, the specific pricing method see Figure 9.Figure 9 Taking three step level water price model, can to some extent, Contain people waste the limited water resources , promote enterprises into taking all kinds of advanced technologies to improve the Comprehensive utilization of water resources, and realize the goal of urban water conservation and limited water resources Sustainable and high-efficiency using and saving. In conclude, it’s an effective and feasible strategy at present.Cost-Benefit Analysis of water-saving society construction1. Cost-Benefit Analyses ModelThe benefit of the water-saving society construction n s B B B −= (15) :s B water use benefit of the whole society in Water-saving condition。