外文文献毕业论文
毕业论文(设计)外文文献翻译及原文

金融体制、融资约束与投资——来自OECD的实证分析R.SemenovDepartment of Economics,University of Nijmegen,Nijmegen(荷兰内梅亨大学,经济学院)这篇论文考查了OECD的11个国家中现金流量对企业投资的影响.我们发现不同国家之间投资对企业内部可获取资金的敏感性具有显著差异,并且银企之间具有明显的紧密关系的国家的敏感性比银企之间具有公平关系的国家的低.同时,我们发现融资约束与整体金融发展指标不存在关系.我们的结论与资本市场信息和激励问题对企业投资具有重要作用这种观点一致,并且紧密的银企关系会减少这些问题从而增加企业获取外部融资的渠道。
一、引言各个国家的企业在显著不同的金融体制下运行。
金融发展水平的差别(例如,相对GDP的信用额度和相对GDP的相应股票市场的资本化程度),在所有者和管理者关系、企业和债权人的模式中,企业控制的市场活动水平可以很好地被记录.在完美资本市场,对于具有正的净现值投资机会的企业将一直获得资金。
然而,经济理论表明市场摩擦,诸如信息不对称和激励问题会使获得外部资本更加昂贵,并且具有盈利投资机会的企业不一定能够获取所需资本.这表明融资要素,例如内部产生资金数量、新债务和权益的可得性,共同决定了企业的投资决策.现今已经有大量考查外部资金可得性对投资决策的影响的实证资料(可参考,例如Fazzari(1998)、 Hoshi(1991)、 Chapman(1996)、Samuel(1998)).大多数研究结果表明金融变量例如现金流量有助于解释企业的投资水平。
这项研究结果解释表明企业投资受限于外部资金的可得性。
很多模型强调运行正常的金融中介和金融市场有助于改善信息不对称和交易成本,减缓不对称问题,从而促使储蓄资金投着长期和高回报的项目,并且提高资源的有效配置(参看Levine(1997)的评论文章)。
因而我们预期用于更加发达的金融体制的国家的企业将更容易获得外部融资.几位学者已经指出建立企业和金融中介机构可进一步缓解金融市场摩擦。
自动化专业毕业论文外文文献翻译

目录Part 1 PID type fuzzy controller and parameters adaptive method (1)Part 2 Application of self adaptation fuzzy-PID control for main steam temperature control system in power station (7)Part 3 Neuro-fuzzy generalized predictive control of boiler steam temperature ..................................................................... (13)Part 4 为Part3译文:锅炉蒸汽温度模糊神经网络的广义预测控制21Part 1 PID type fuzzy controller and Parametersadaptive methodWu zhi QIAO, Masaharu MizumotoAbstract: The authors of this paper try to analyze the dynamic behavior of the product-sum crisp type fuzzy controller, revealing that this type of fuzzy controller behaves approximately like a PD controller that may yield steady-state error for the control system. By relating to the conventional PID control theory, we propose a new fuzzy controller structure, namely PID type fuzzy controller which retains the characteristics similar to the conventional PID controller. In order to improve further the performance of the fuzzy controller, we work out a method to tune the parameters of the PID type fuzzy controller on line, producing a parameter adaptive fuzzy controller. Simulation experiments are made to demonstrate the fine performance of these novel fuzzy controller structures.Keywords: Fuzzy controller; PID control; Adaptive control1. IntroductionAmong various inference methods used in the fuzzy controller found in literatures , the most widely used ones in practice are the Mamdani method proposed by Mamdani and his associates who adopted the Min-max compositional rule of inference based on an interpretation of a control rule as a conjunction of the antecedent and consequent, and the product-sum method proposed by Mizumoto who suggested to introduce the product and arithmetic mean aggregation operators to replace the logical AND (minimum) and OR (maximum) calculations in the Min-max compositional rule of inference.In the algorithm of a fuzzy controller, the fuzzy function calculation is also a complicated and time consuming task. Tagagi and Sugeno proposed a crisp type model in which the consequent parts of the fuzzy control rules are crisp functional representation or crisp real numbers in the simplified case instead of fuzzy sets . With this model of crisp real number output, the fuzzy set of the inference consequence willbe a discrete fuzzy set with a finite number of points, this can greatly simplify the fuzzy function algorithm.Both the Min-max method and the product-sum method are often applied with the crisp output model in a mixed manner. Especially the mixed product-sum crisp model has a fine performance and the simplest algorithm that is very easy to be implemented in hardware system and converted into a fuzzy neural network model. In this paper, we will take account of the product-sum crisp type fuzzy controller.2. PID type fuzzy controller structureAs illustrated in previous sections, the PD function approximately behaves like a parameter time-varying PD controller. Since the mathematical models of most industrial process systems are of type, obviously there would exist an steady-state error if they are controlled by this kind of fuzzy controller. This characteristic has been stated in the brief review of the PID controller in the previous section.If we want to eliminate the steady-state error of the control system, we can imagine to substitute the input (the change rate of error or the derivative of error) of the fuzzy controller with the integration of error. This will result the fuzzy controller behaving like a parameter time-varying PI controller, thus the steady-state error is expelled by the integration action. However, a PI type fuzzy controller will have a slow rise time if the P parameters are chosen small, and have a large overshoot if the P or I parameters are chosen large. So there may be the time when one wants to introduce not only the integration control but the derivative control to the fuzzy control system, because the derivative control can reduce the overshoot of the system's response so as to improve the control performance. Of course this can be realized by designing a fuzzy controller with three inputs, error, the change rate of error and the integration of error. However, these methods will be hard to implement in practice because of the difficulty in constructing fuzzy control rules. Usually fuzzy control rules are constructed by summarizing the manual control experience of an operator who has been controlling the industrial process skillfully and successfully. The operator intuitively regulates the executor to control the process by watching theerror and the change rate of the error between the system's output and the set-point value. It is not the practice for the operator to observe the integration of error. Moreover, adding one input variable will greatly increase the number of control rules, the constructing of fuzzy control rules are even more difficult task and it needs more computation efforts. Hence we may want to design a fuzzy controller that possesses the fine characteristics of the PID controller by using only the error and the change rate of error as its inputs.One way is to have an integrator serially connected to the output of the fuzzy controller as shown in Fig. 1. In Fig. 1,1K and 2K are scaling factors for e and ~ respectively, and fl is the integral constant. In the proceeding text, for convenience, we did not consider the scaling factors. Here in Fig. 2, when we look at the neighborhood of NODE point in the e - ~ plane, it follows from (1) that the control input to the plant can be approximated by(1)Hence the fuzzy controller becomes a parameter time-varying PI controller, itsequivalent proportional control and integral control components are BK2D and ilK1 P respectively. We call this fuzzy controller as the PI type fuzzy controller (PI fc). We can hope that in a PI type fuzzy control system, the steady-state error becomes zero.To verify the property of the PI type fuzzy controller, we carry out some simulation experiments. Before presenting the simulation, we give a description of the simulation model. In the fuzzy control system shown in Fig. 3, the plant model is a second-order and type system with the following transfer function:)1)(1()(21++=s T s T K s G (2) Where K = 16, 1T = 1, and 2T = 0.5. In our simulation experiments, we use thediscrete simulation method, the results would be slightly different from that of a continuous system, the sampling time of the system is set to be 0.1 s. For the fuzzy controller, the fuzzy subsets of e and d are defined as shown in Fig. 4. Their coresThe fuzzy control rules are represented as Table 1. Fig. 5 demonstrates the simulation result of step response of the fuzzy control system with a Pl fc. We can see that the steady-state error of the control system becomes zero, but when the integration factor fl is small, the system's response is slow, and when it is too large, there is a high overshoot and serious oscillation. Therefore, we may want to introduce the derivative control law into the fuzzy controller to overcome the overshoot and instability. We propose a controller structure that simply connects the PD type and the PI type fuzzy controller together in parallel. We have the equivalent structure of that by connecting a PI device with the basic fuzzy controller serially as shown in Fig.6. Where ~ is the weight on PD type fuzzy controller and fi is that on PI type fuzzy controller, the larger a/fi means more emphasis on the derivative control and less emphasis on the integration control, and vice versa. It follows from (7) that the output of the fuzzy controller is(3)3. The parameter adaptive methodThus the fuzzy controller behaves like a time-varying PID controller, its equivalent proportional control, integral control and derivative control components are respectively. We call this new controller structure a PID type fuzzy controller (PID fc). Figs. 7 and 8 are the simulation results of the system's step response of such control system. The influence of ~ and fl to the system performance is illustrated. When ~ > 0 and/3 = 0, meaning that the fuzzy controller behaves like PD fc, there exist a steady-state error. When ~ = 0 and fl > 0, meaning that the fuzzy controller behaves like a PI fc, the steady-state error of the system is eliminated but there is a large overshoot and serious oscillation.When ~ > 0 and 13 > 0 the fuzzy controller becomes a PID fc, the overshoot is substantially reduced. It is possible to get a comparatively good performance by carefully choosing the value of αandβ.4. ConclusionsWe have studied the input-output behavior of the product-sum crisp type fuzzy controller, revealing that this type of fuzzy controller behaves approximately like a parameter time-varying PD controller. Therefore, the analysis and designing of a fuzzy control system can take advantage of the conventional PID control theory. According to the coventional PID control theory, we have been able to propose some improvement methods for the crisp type fuzzy controller.It has been illustrated that the PD type fuzzy controller yields a steady-state error for the type system, the PI type fuzzy controller can eliminate the steady-state error. We proposed a controller structure, that combines the features of both PD type and PI type fuzzy controller, obtaining a PID type fuzzy controller which allows the control system to have a fast rise and a small overshoot as well as a short settling time.To improve further the performance of the proposed PID type fuzzy controller, the authors designed a parameter adaptive fuzzy controller. The PID type fuzzy controller can be decomposed into the equivalent proportional control, integral control and the derivative control components. The proposed parameter adaptive fuzzy controller decreases the equivalent integral control component of the fuzzy controller gradually with the system response process time, so as to increase the damping of the system when the system is about to settle down, meanwhile keeps the proportional control component unchanged so as to guarantee quick reaction against the system's error. With the parameter adaptive fuzzy controller, the oscillation of the system is strongly restrained and the settling time is shortened considerably.We have presented the simulation results to demonstrate the fine performance of the proposed PID type fuzzy controller and the parameter adaptive fuzzy controller structure.Part 2 Application of self adaptation fuzzy-PID control for main steam temperature control system inpower stationZHI-BIN LIAbstract: In light of the large delay, strong inertia, and uncertainty characteristics of main steam temperature process, a self adaptation fuzzy-PID serial control system is presented, which not only contains the anti-disturbance performance of serial control, but also combines the good dynamic performance of fuzzy control. The simulation results show that this control system has more quickly response, better precision and stronger anti-disturbance ability.Keywords:Main steam temperature;Self adaptation;Fuzzy control;Serial control1. IntroductionThe boiler superheaters of modem thermal power station run under the condition of high temperature and high pressure, and the superheater’s temperature is highest in the steam channels.so it has important effect to the running of the whole thermal power station.If the temperature is too high, it will be probably burnt out. If the temperature is too low ,the efficiency will be reduced So the main steam temperature mast be strictly controlled near the given value.Fig l shows the boiler main steam temperature system structure.Fig.1 boiler main steam temperature systemIt can be concluded from Fig l that a good main steam temperature controlsystem not only has adequately quickly response to flue disturbance and load fluctuation, but also has strong control ability to desuperheating water disturbance. The general control scheme is serial PID control or double loop control system with derivative. But when the work condition and external disturbance change large, the performance will become instable. This paper presents a self adaptation fuzzy-PID serial control system. which not only contains the anti-disturbance performance of serial control, but also combines the good dynamic character and quickly response of fuzzy control .1. Design of Control SystemThe general regulation adopts serial PID control system with load feed forward .which assures that the main steam temperature is near the given value 540℃in most condition .If parameter of PID control changeless and the work condition and external disturbance change large, the performance will become in stable .The fuzzy control is fit for controlling non-linear and uncertain process. The general fuzzy controller takes error E and error change ratio EC as input variables .actually it is a non-linear PD controller, so it has the good dynamic performance .But the steady error is still in existence. In linear system theory, integral can eliminate the steady error. So if fuzzy control is combined with PI control, not only contains the anti-disturbance performance of serial control, but also has the good dynamic performance and quickly response.In order to improve fuzzy control self adaptation ability, Prof .Long Sheng-Zhao and Wang Pei-zhuang take the located in bringing forward a new idea which can modify the control regulation online .This regulation is:]1,0[,)1(∈-+=αααEC E UThis control regulation depends on only one parameter α.Once αis fixed .the weight of E and EC will be fixed and the self adaptation ability will be very small .It was improved by Prof. Li Dong-hui and the new regulation is as follow;]1,0[,,,3,)1(2,)1(1,)1(0,)1({321033221100∈±=-+±=-+±=-+=-+=ααααααααααααE EC E E EC E E EC E E EC E UBecause it is very difficult to find a self of optimum parameter, a new method is presented by Prof .Zhou Xian-Lan, the regulation is as follow:)0(),ex p(12>--=k ke αBut this algorithm still can not eliminate the steady error .This paper combines this algorithm with PI control ,the performance is improved .2. Simulation of Control System3.1 Dynamic character of controlled objectPapers should be limited to 6 pages Papers longer than 6 pages will be subject to extra fees based on their length .Fig .2 main steam temperature control system structureFig 2 shows the main steam temperature control system structure ,)(),(21s W s W δδare main controller and auxiliary controller,)(),(21s W s W o o are characters of the leading and inertia sections,)(),(21s W s W H H are measure unit.3.2 Simulation of the general serial PID control systemThe simulation of the general serial PID control system is operated by MATLAB, the simulation modal is as Fig.3.Setp1 and Setp2 are the given value disturbance and superheating water disturb & rice .PID Controller1 and PID Controller2 are main controller and auxiliary controller .The parameter value which comes from references is as follow :667.37,074.0,33.31)(25)(111111122===++===D I p D I p p k k k s k sk k s W k s W δδFig.3. the general PID control system simulation modal3.3 Simulation of self adaptation fuzzy-PID control system SpacingThe simulation modal is as Fig 4.Auxiliary controller is:25)(22==p k s W δ.Main controller is Fuzzy-PI structure, and the PI controller is:074.0,33.31)(11111==+=I p I p k k s k k s W δFuzzy controller is realized by S-function, and the code is as fig.5.Fig.4. the fuzzy PID control system simulation modalFig 5 the S-function code of fuzzy control3.4 Comparison of the simulationGiven the same given value disturbance and the superheating water disturbance,we compare the response of fuzzy-PID control system with PID serial control system. The simulation results are as fig.6-7.From Fig6-7,we can conclude that the self adaptation fuzzy-PID control system has the more quickly response, smaller excess and stronger anti-disturbance.4. Conclusion(1)Because it combines the advantage of PID controller and fuzzy controller, theself adaptation fuzzy-PID control system has better performance than the general PID serial control system.(2)The parameter can self adjust according to the error E value. so this kind of controller can harmonize quickly response with system stability.Part 3 Neuro-fuzzy generalized predictive controlof boiler steam temperatureXiangjie LIU, Jizhen LIU, Ping GUANAbstract: Power plants are nonlinear and uncertain complex systems. Reliable control of superheated steam temperature is necessary to ensure high efficiency and high load-following capability in the operation of modern power plant. A nonlinear generalized predictive controller based on neuro-fuzzy network (NFGPC) is proposed in this paper. The proposed nonlinear controller is applied to control the superheated steam temperature of a 200MW power plant. From the experiments on the plant and the simulation of the plant, much better performance than the traditional controller is obtained.Keywords: Neuro-fuzzy networks; Generalized predictive control; Superheated steam temperature1. IntroductionContinuous process in power plant and power station are complex systems characterized by nonlinearity, uncertainty and load disturbance. The superheater is an important part of the steam generation process in the boiler-turbine system, where steam is superheated before entering the turbine that drives the generator. Controlling superheated steam temperature is not only technically challenging, but also economically important.From Fig.1,the steam generated from the boiler drum passes through the low-temperature superheater before it enters the radiant-type platen superheater. Water is sprayed onto the steam to control the superheated steam temperature in both the low and high temperature superheaters. Proper control of the superheated steam temperature is extremely important to ensure the overall efficiency and safety of the power plant. It is undesirable that the steam temperature is too high, as it can damage the superheater and the high pressure turbine, or too low, as it will lower the efficiency of the power plant. It is also important to reduce the temperaturefluctuations inside the superheater, as it helps to minimize mechanical stress that causes micro-cracks in the unit, in order to prolong the life of the unit and to reduce maintenance costs. As the GPC is derived by minimizing these fluctuations, it is amongst the controllers that are most suitable for achieving this goal.The multivariable multi-step adaptive regulator has been applied to control the superheated steam temperature in a 150 t/h boiler, and generalized predictive control was proposed to control the steam temperature. A nonlinear long-range predictive controller based on neural networks is developed into control the main steam temperature and pressure, and the reheated steam temperature at several operating levels. The control of the main steam pressure and temperature based on a nonlinear model that consists of nonlinear static constants and linear dynamics is presented in that.Fig.1 The boiler and superheater steam generation process Fuzzy logic is capable of incorporating human experiences via the fuzzy rules. Nevertheless, the design of fuzzy logic controllers is somehow time consuming, as the fuzzy rules are often obtained by trials and errors. In contrast, neural networks not only have the ability to approximate non-linear functions with arbitrary accuracy, they can also be trained from experimental data. The neuro-fuzzy networks developed recently have the advantages of model transparency of fuzzy logic and learning capability of neural networks. The NFN is have been used to develop self-tuning control, and is therefore a useful tool for developing nonlinear predictive control. Since NFN is can be considered as a network that consists of several local re-gions, each of which contains a local linear model, nonlinear predictive control based onNFN can be devised with the network incorporating all the local generalized predictive controllers (GPC) designed using the respective local linear models. Following this approach, the nonlinear generalized predictive controllers based on the NFN, or simply, the neuro-fuzzy generalized predictive controllers (NFG-PCs)are derived here. The proposed controller is then applied to control the superheated steam temperature of the 200MW power unit. Experimental data obtained from the plant are used to train the NFN model, and from which local GPC that form part of the NFGPC is then designed. The proposed controller is tested first on the simulation of the process, before applying it to control the power plant.2. Neuro-fuzzy network modellingConsider the following general single-input single-output nonlinear dynamic system:),1(),...,(),(),...,1([)(''+-----=uy n d t u d t u n t y t y f t y ∆+--/)()](),...,1('t e n t e t e e (1)where f[.]is a smooth nonlinear function such that a Taylor series expansion exists, e(t)is a zero mean white noise and Δis the differencing operator,''',,e u y n n n and d are respectively the known orders and time delay of the system. Let the local linear model of the nonlinear system (1) at the operating point )(t o be given by the following Controlled Auto-Regressive Integrated Moving Average (CARIMA) model:)()()()()()(111t e z C t u z B z t y z A d ----+∆= (2) Where )()(),()(1111----∆=z andC z B z A z A are polynomials in 1-z , the backward shift operator. Note that the coefficients of these polynomials are a function of the operating point )(t o .The nonlinear system (1) is partitioned into several operating regions, such that each region can be approximated by a local linear model. Since NFN is a class of associative memory networks with knowledge stored locally, they can be applied to model this class of nonlinear systems. A schematic diagram of the NFN is shown in Fig.2.B-spline functions are used as the membership functions in theNFN for the following reasons. First, B-spline functions can be readily specified by the order of the basis function and the number of inner knots. Second, they are defined on a bounded support, and the output of the basis function is always positive, i.e.,],[,0)(j k j j k x x λλμ-∉=and ],[,0)(j k j j k x x λλμ-∈>.Third, the basis functions form a partition of unity, i.e.,.][,1)(min,∑∈≡j mam j k x x x x μ(3)And fourth, the output of the basis functions can be obtained by a recurrence equation.Fig. 2 neuro-fuzzy network The membership functions of the fuzzy variables derived from the fuzzy rules can be obtained by the tensor product of the univariate basis functions. As an example, consider the NFN shown in Fig.2, which consists of the following fuzzy rules: IF operating condition i (1x is positive small, ... , and n x is negative large),THEN the output is given by the local CARIMA model i:...)()(ˆ...)1(ˆ)(ˆ01+-∆+-++-=d t u b n t y a t y a t yi i a i in i i i a )(...)()(c i in i b i in n t e c t e n d t u b c b -+++--∆+ (4)or )()()()()(ˆ)(111t e z C t u z B z t yz A i i i i d i i ----+∆= (5) Where )()(),(111---z andC z B z A i i i are polynomials in the backward shift operator 1-z , and d is the dead time of the plant,)(t u i is the control, and )(t e i is a zero mean independent random variable with a variance of 2δ. The multivariate basis function )(k i x a is obtained by the tensor products of the univariate basis functions,p i x A a nk k i k i ,...,2,1,)(1==∏=μ (6)where n is the dimension of the input vector x , and p , the total number of weights in the NFN, is given by,∏=+=nk i i k R p 1)( (7)Where i k and i R are the order of the basis function and the number of inner knots respectively. The properties of the univariate B-spline basis functions described previously also apply to the multivariate basis function, which is defined on the hyper-rectangles. The output of the NFN is,∑∑∑=====p i i i p i ip i i i a y aa yy 111ˆˆˆ (8) 3. Neuro-fuzzy modelling and predictive control of superheatedsteam temperatureLet θbe the superheated steam temperature, and θμ, the flow of spray water to the high temperature superheater. The response of θcan be approximated by a second order model:The linear models, however, only a local model for the selected operating point. Since load is the unique antecedent variable, it is used to select the division between the local regions in the NFN. Based on this approach, the load is divided into five regions as shown in Fig.3,using also the experience of the operators, who regard a load of 200MW as high,180MW as medium high,160MW as medium,140MW as medium low and 120MW as low. For a sampling interval of 30s , the estimated linear local models )(1-z A used in the NFN are shown in Table 1.Fig. 3 Membership function for local modelsTable 1 Local CARIMA models in neuro-fuzzy modelCascade control scheme is widely used to control the superheated steam temperature. Feed forward control, with the steam flow and the gas temperature as inputs, can be applied to provide a faster response to large variations in these two variables. In practice, the feed forward paths are activated only when there are significant changes in these variables. The control scheme also prevents the faster dynamics of the plant, i.e., the spray water valve and the water/steam mixing, from affecting the slower dynamics of the plant, i.e., the high temperature superheater. With the global nonlinear NFN model in Table 1, the proposed NFGPC scheme is shown in Fig.4.Fig. 4 NFGPC control of superheated steam temperature with feed-for-ward control.As a further illustration, the power plant is simulated using the NFN model given in Table 1,and is controlled respectively by the NFGPC, the conventional linear GPC controller, and the cascaded PI controller while the load changes from 160MW to 200MW.The conventional linear GPC controller is the local controller designed for the“medium”operating region. The results are shown in Fig.5,showing that, as expected, the best performance is obtained from the NFGPC as it is designed based on a more accurate process model. This is followed by the conventional linear GPC controller. The performance of the conventional cascade PI controller is the worst, indicating that it is unable to control satisfactory the superheated steam temperature under large load changes. This may be the reason for controlling the power plant manually when there are large load changes.Fig.5 comparison of the NFGPC, conventional linear GPC, and cascade PI controller.4. ConclusionsThe modeling and control of a 200 MW power plant using the neuro-fuzzy approach is presented in this paper. The NFN consists of five local CARIMA models.The out-put of the network is the interpolation of the local models using memberships given by the B-spline basis functions. The proposed NFGPC is similarly constructed, which is designed from the CARIMA models in the NFN. The NFGPC is most suitable for processes with smooth nonlinearity, such that its full operating range can be partitioned into several local linear operating regions. The proposed NFGPC therefore provides a useful alternative for controlling this class of nonlinear power plants, which are formerly difficult to be controlled using traditional methods.Part 4 为Part3译文:锅炉蒸汽温度模糊神经网络的广义预测控制Xiangjie LIU, Jizhen LIU, Ping GUAN摘要:发电厂是非线性和不确定性的复杂系统。
《毕业论文中引用外文文献的技巧》

《毕业论文中引用外文文献的技巧》在撰写毕业论文时,引用外文文献是非常常见的情况。
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然而,许多学生在引用外文文献时常常遇到困惑和困难。
本文将介绍毕业论文中引用外文文献的技巧,帮助读者正确、规范地引用外文文献,提升论文的质量。
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总之,正确地引用外文文献是撰写毕业论文的重要环节,需要认真对待。
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浙江大学本科毕业论文外文文献翻译

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未经允许,请勿外传!浙江大学本科毕业论文外文文献翻译The influence of political connections on the firm value of small and medium-sized enterprises in China政治关联在中国对中小型企业价值的影响1摘要中小型企业的价值受很多因素的影响,比如股东、现金流以及政治关联等.这篇文章调查的正是在中国政治关联对中小型企业价值的影响。
通过实验数据来分析政治关联对企业价值效益的影响.结果表明政府关联是关键的因素并且在中国对中小型企业的价值具有负面影响。
2重要内容翻译2。
1引言在商业界,有越来越多关于政治关联的影响的经济研究。
它们发现政治关联能够帮助企业确保有利的规章条件以及成功获得资源,比如能够最终提高企业价值或是提升绩效的银行贷款,这种政治关联的影响在不同的经济条件下呈现不同的效果。
在高腐败和法律制度薄弱的国家,政治关联对企业价值具有决定性因素1的作用.中国由高度集权的计划经济向市场经济转变,政府对市场具有较强的控制作用,而且有大量的上市企业具有政治关联。
中小型企业发展的很迅速,他们已经在全球经济环境中变得越来越重要。
从90年代起, 政治因素对中国的任何规模的企业来说都变得越来越重要,尤其是中小型企业的价值。
和其他的部门相比较,中小型企业只有较小的现金流,不稳定的现金流且高负债率.一方面,中小型企业改变更加灵活;另一方面,中小型企业在由于企业规模以及对银行来说没有可以抵押的资产,在筹资方面较为困难。
企业如何应对微观经济环境和政策去保证正常的企业活动,并且政治关联如何影响企业价值?这篇论文调查政治关联和企业价值之间的联系,并且试图去研究企业是否可以从政治关联中获利提升企业价值。
2.2定义这些中小型企业之所以叫中小型企业,是和管理规模有关。
对这些小企业来说,雇员很少,营业额较低,资金一般由较少的人提供,因此,通常由这些业主直接管理企业。
毕业论文英文参考文献与译文

Inventory managementInventory ControlOn the so-called "inventory control", many people will interpret it as a "storage management", which is actually a big distortion.The traditional narrow view, mainly for warehouse inventory control of materials for inventory, data processing, storage, distribution, etc., through the implementation of anti-corrosion, temperature and humidity control means, to make the custody of the physical inventory to maintain optimum purposes. This is just a form of inventory control, or can be defined as the physical inventory control. How, then, from a broad perspective to understand inventory control? Inventory control should be related to the company's financial and operational objectives, in particular operating cash flow by optimizing the entire demand and supply chain management processes (DSCM), a reasonable set of ERP control strategy, and supported by appropriate information processing tools, tools to achieved in ensuring the timely delivery of the premise, as far as possible to reduce inventory levels, reducing inventory and obsolescence, the risk of devaluation. In this sense, the physical inventory control to achieve financial goals is just a means to control the entire inventory or just a necessary part; from the perspective of organizational functions, physical inventory control, warehouse management is mainly the responsibility of The broad inventory control is the demand and supply chain management, and the whole company's responsibility.Why until now many people's understanding of inventory control, limited physical inventory control? The following two reasons can not be ignored:First, our enterprises do not attach importance to inventory control. Especially those who benefit relatively good business, as long as there is money on the few people to consider the problem of inventory turnover. Inventory control is simply interpreted as warehouse management, unless the time to spend money, it may have been to see the inventory problem, and see the results are often very simple procurement to buy more, or did not do warehouse departments .Second, ERP misleading. Invoicing software is simple audacity to call it ERP, companies on their so-called ERP can reduce the number of inventory, inventory control, seems to rely on their small software can get. Even as SAP, BAAN ERP world, the field ofthese big boys, but also their simple modules inside the warehouse management functionality is defined as "inventory management" or "inventory control." This makes the already not quite understand what our inventory control, but not sure what is inventory control.In fact, from the perspective of broadly understood, inventory control, shouldinclude the following:First, the fundamental purpose of inventory control. We know that the so-called world-class manufacturing, two key assessment indicators (KPI) is, customer satisfaction and inventory turns, inventory turns and this is actually the fundamental objective of inventory control.Second, inventory control means. Increase inventory turns, relying solely on the so-called physical inventory control is not enough, it should be the demand and supply chain management process flow of this large output, and this big warehouse management processes in addition to including this link, the more important The section also includes: forecasting and order processing, production planning and control, materials planning and purchasing control, inventory planning and forecasting in itself, as well as finished products, raw materials, distribution and delivery of the strategy, and even customs management processes.And with the demand and supply chain management processes throughout the process, it is the information flow and capital flow management. In other words, inventory itself is across the entire demand and supply management processes in all aspects of inventory control in order to achieve the fundamental purpose, it must control all aspects of inventory, rather than just manage the physical inventory at hand.Third, inventory control, organizational structure and assessment.Since inventory control is the demand and supply chain management processes, output, inventory control to achieve the fundamental purpose of this process must be compatible with a rational organizational structure. Until now, we can see that many companies have only one purchasing department, purchasing department following pipe warehouse. This is far short of inventory control requirements. From the demand and supply chain management process analysis, we know that purchasing and warehouse management is the executive arm of the typical, and inventory control should focus on prevention, the executive branch is very difficult to "prevent inventory" for the simple reason that they assessment indicatorsin large part to ensure supply (production, customer). How the actual situation, a reasonable demand and supply chain management processes, and thus set the corresponding rational organizational structure and is a question many of our enterprisesto exploreThe role of inventory controlInventory management is an important part of business management. In the production and operation activities, inventory management must ensure that both the production plant for raw materials, spare parts demand, but also directly affect the purchasing, sales of share, sales activities. To make an inventory of corporate liquidity, accelerate cash flow, the security of supply under the premise of minimizing Yaku funds, directly affects the operational efficiency. Ensure the production and operation needs of the premise, so keep inventories at a reasonable level; dynamic inventory control, timely, appropriate proposed order to avoid over storage or out of stock; reduce inventory footprint, lower total cost of inventory; control stock funds used to accelerate cash flow.Problems arising from excessive inventory: increased warehouse space andinventory storage costs, thereby increasing product costs; take a lot of liquidity, resultingin sluggish capital, not only increased the burden of payment of interest, etc., would affect the time value of money and opportunity income; finished products and raw materials caused by physical loss and intangible losses; a large number of enterprise resource idle, affecting their rational allocation and optimization; cover the production, operation of the whole process of the various contradictions and problems, is not conducive to improve the management level.Inventory is too small the resulting problems: service levels caused a decline in the profit impact of marketing and corporate reputation; production system caused by inadequate supply of raw materials or other materials, affecting the normal production process; to shorten lead times, increase the number of orders, so order (production) costs; affect the balance of production and assembly of complete sets.NotesInventory management should particularly consider the following two questions:First, according to sales plans, according to the planned production of the goods circulated in the market, we should consider where, how much storage.Second, starting from the level of service and economic benefits to determine howto ensure inventories and supplementary questions.The two problems with the inventory in the logistics process functions.In general, the inventory function:(1)to prevent interrupted. Received orders to shorten the delivery of goods fromthe time in order to ensure quality service, at the same time to prevent out of stock.(2)to ensure proper inventory levels, saving inventory costs.(3)to reduce logistics costs. Supplement with the appropriate time interval compatible with the reasonable demand of the cargo in order to reduce logistics costs, eliminate or avoid sales fluctuations.(4)ensure the production planning, smooth to eliminate or avoid sales fluctuations.(5)display function.(6)reserve. Mass storage when the price falls, reduce losses, to respond to disasters and other contingencies.About the warehouse (inventory) on what the question, we must consider the number and location. If the distribution center, it should be possible according to customer needs, set at an appropriate place; if it is stored in central places to minimize the complementary principle to the distribution centers, there is no place certain requirements. When the stock base is established, will have to take into account are stored in various locations in what commodities.库存管理库存控制在谈到所谓“库存控制”的时候,很多人将其理解为“仓储管理”,这实际上是个很大的曲解。
毕业论文外文文献翻译要求

毕业论文外文文献翻译要求
一、翻译的外文文献可以是一篇,也可以是两篇,但英文字符要求不少于2万
二、翻译的外文文献应主要选自学术期刊、学术会议的文章、有关著作及其他相关材料,应与毕业论文(设计)主题相关,并在中文译文首页用“脚注”形式注明原文作者及出处,外文原文后应附中文译文。
三、中文译文的基本撰写格式为:
1.题目:采用三号、黑体字、居中打印;
2.正文:采用小四号、宋体字,行间距一般为固定值20磅,标准字符间距。
页边距为左3cm,右2.5cm,上下各2.5cm,页面统一采用A4纸。
四、英文的基本撰写格式为:
1.题目:采用三号、Times New Roman字、加黑、居中打印
2.正文:采用小四号、Times New Roman字。
行间距一般为固定值20磅,标准字符间距。
页边距为左3cm,右2.5cm,上下各2.5cm,页面统一采用A4纸.
3.脚注:五号,Times New Roman,顺序为作者.题目.出处,
五、封面格式由学校统一制作(注:封面上的“翻译题目”指中文译文的题目,封面中文小四号宋体,英文小四号Times New Roman),
六、装订:左侧均匀装订,上下共两个钉,并按“封面、外文原文、译文”的顺序统一装订。
七、忌自行更改表格样式
大连工业大学艺术与信息工程学院
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毕业设计论文外文文献翻译

毕业设计(论文)外文文献翻译院系:财务与会计学院年级专业:201*级财务管理姓名:学号:132148***附件: 财务风险管理【Abstract】Although financial risk has increased significantly in recent years risk and risk management are not contemporary issues。
The result of increasingly global markets is that risk may originate with events thousands of miles away that have nothing to do with the domestic market。
Information is available instantaneously which means that change and subsequent market reactions occur very quickly。
The economic climate and markets can be affected very quickly by changes in exchange rates interest rates and commodity prices。
Counterparties can rapidly become problematic。
As a result it is important to ensure financial risks are identified and managed appropriately. Preparation is a key component of risk management。
【Key Words】Financial risk,Risk management,YieldsI. Financial risks arising1.1What Is Risk1.1.1The concept of riskRisk provides the basis for opportunity. The terms risk and exposure have subtle differences in their meaning. Risk refers to the probability of loss while exposure is the possibility of loss although they are often used interchangeably。
毕业论文外文文献翻译

2013届本科生毕业论文英文参考文献翻译
Oracle虚拟机服务器软件虚拟化在一个64位
Linux环境的性能和可扩展性
(译文)
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信息工程
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完成日期:
2013年6月
Oracle虚拟机服务器软件虚拟化在一个64位Linux环境的性能和可扩展性
benefits, however, this has not been without its attendantproblems and anomalies, such as performance tuning anderratic performance metrics, unresponsive virtualized systems,crashed virtualized servers, misconfigured virtual hostingplatforms, amongst others. The focus of this research was theanalysis of the performance of the Oracle VM servervirtualization platform against that of the bare-metal serverenvironment. The scalability and its support for high volumetransactions were also analyzed using 30 and 50 active usersfor the performance evaluation. Swingbench and LMbench,two open suite benchmark tools were utilized in measuringperformance. Scalability was also measured using Swingbench.Evidential results gathered from Swingbench revealed 4% and8% overhead for 30 and 50 active users respectively in theperformance evaluation of Oracle database in a single OracleVM. Correspondingly, performance metric法
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毕业论文(设计)外文翻译题目:昌九一体化背景下的金融一体化研究一、外文原文DOES LOCAL FINANCIAL DEVELOPMENT MATTER?We study the effects of differences in local financial development within an integrated financial market. We construct a new indicator of financial development by estimating a regional effect on the probability that, ceteris paribus, a household is shut off from the credit market. By using this indicator we find that financial development enhances the probability an individual starts his own business, favors entry, increases competition, and promotes growth of firms. As predicted by theory, these effects are weaker for larger firms, which can more easily raise funds outside of the local area. These effects are present even when we instrument our indicator with the structure of the local banking markets in 1936, which, because of regulatory reasons, affected the supply of credit in the following 50 years. Overall, the results suggest local financial development is an important determinant of the economic success of an area even in an environment where there are no frictions to capital movements.Since the seminal work of King and Levine (1993), a large body of empirical evidence has shown that a country’s level of financial development impacts its ability to grow.1 Much ofthis evidence, however, comes from a period when cross-border capital movements were very limited. In the last decade, international capital mobility has exploded. Private capital flow to emerging market economies have grown from close to nothing in the 1970s, to 170 billion in the 1980s, to 1.3 trillions in the 1990s.2 During the same period the amount of U.S. private equity money invested abroad and the number of foreign firms listed in the United States has experienced a similar growth rate. The phenomenon is so dramatic that many countries have started wondering whether they need a national stock market once their firms can list on NASDAQ.In light of these changes, the question of whether national financial institutions andmarkets still matter for growth once domestic agents have access to foreign markets has become very important from a policy perspective. Unfortunately, it is a difficult question to answer empirically. The integration of national financial markets is so recent that we lack a sufficiently long time series to estimate its impact in the data. At the same time, the pace of integration is so fast that if we were to establish that national financial development mattered for national growth during the last decade, we could not confidently extrapolate this result to the current decade.To try and assess the relevance for growth of national financial institutions and marketsin an increasingly integrated capital market we follow a different approach. Rather than studying the effect of financial development across countries we study the effect of local financial development within a single country, which has being unified, from both a political and a regulatory point of view, for the last 140 years: Italy. The level of integration reached within Italy probably represents an upper bound for the level of integration international financial markets can reach. Hence, if we find that local financial development matters for growth within Italy, we can safely conclude national financial development will continue to matter for national growth in the foreseeable future. Of course, the converse is not true. If we do not find the effect within Italy, it is still possible that the effect is present across countries.Moving the focus from cross-country comparisons to within country analysis exacerbates some of the problems also present in the cross-country analysis. A first challenge is to find an appropriate measure of financial development. Measures such as stock market capitalization to GDP or stock market turnover to GDP make no sense when applied at the local level. We address this problem by developing a new indicator, which enables us to measure financial development at the local level, relying on the theoretically-sound notion that developed financial markets grant individuals and firms an easier access to external funds.Second, cross-country comparisons assume that differences in financial development areexogenously determined. This assumption becomes more questionable when we move to within country differences: across countries one can hope that exogenous differences in history, culture,and regulation drive differences in financial development. This is harder to imagine within acountry. We address this problem by instrumenting our indicator with some variables that describe the regional characteristics of the banking system as of 1936. The Banking Law introduced in 1936, which was intended to protect the banking system from instability, strictly regulated entry up to the middle 1980s. Since the law treated different types of institutions(savings and loans and national banks) differently, the composition of branches in 1936 greatly influenced the availability of branches in the subsequent 50years. Hence, we use the structure of the banking market in 1936 as an instrument for the exogenous variation in the supply of credit in the 1990, when the market was fully deregulated.Moving the focus from cross-country comparisons to within country analysis alsoprovides new opportunities. Rather than restricting our analysis to the macro effect of financial development we also study its micro effects, showing its impact on individual households and4 firms. We then study how this micro effect translates into a macro effect. If financial development affects economic growth by facilitating the creation of new firms, it must be the case that in more financially developed areas it is easier for an individual to become an entrepreneur and, at the same time, these areas should experience a higher rate o f new firms’creation. In doing so, we provide additional support to the causal link between finance and growth, showing the mechanisms through which this link operates.We find strong effects of local financial development. Ceteris paribus an individu al’sodds of starting a business increases by 5.6 percent if he moves from the least financiallydeveloped region to the most financially developed one. Furthermore, he is able to do so at ayounger age. As a result, on average entrepreneurs are 5 years younger in the most financiallydeveloped region than in the least financially developed one. Similarly, the ratio of new firms to population is .46 percentage points higher in the most financially developed provinces than in the least financially developed, and the number of existing firms divided by population is almost two standard deviation higher. In more financially developed regions firms exceed the rate of growth that can be financed internally 67% more than in the least financially developed ones. Interestingly, this effect is entirely concentrated among small and medium firms. This is consistent with the view that larger firms can easily raise funds outside of the area they are located in.Finally, in the most financially developed region per capita GDP grows 2% per annum more than in the least financially developed one.Overall all the evidence suggests that local financial development plays an important role even in a perfectly integrated market. Hence, finance effects are not likely to disappear as the world become more integrated or as Europe becomes unified.While there is a large literature on financial development and growth across countries(see the excellent survey by Levine (1997)), the only papers we know of that studies withincountry differences are Jayaratne and Strahan (1996) and Dehejia and Lleras-Muney (2003).Using the de-regulation of banking in different states of the United States between 1972 and 1991 as a proxy for a quantum jump in financial development, Jayaratne and Strahan (1996) show that annual growth rates in a state increased by 0.51 to 1.19 percentage points a year after deregulation. Dehejia and Lleras-Muney (2003) study the impact of changes in banking regulation on financial development between 1900 and 1940. Both papers show that local financial development matters. They do that, however, in a financial market that was not perfectly integrated yet. In fact, even in Jayaratne and Strahan (1996)’s sample period there were still differences in banking regulation across states and interstate branching was restricted. By contrast, during our sample period there was no difference in regulation across Italian regions nor was interregional lending restricted.The rest of the paper proceeds as follows. Section 1 describes the data. Section 2 introduces our measure of financial development and discusses its robustness. Section 3 analyzes the effects of financial development on firms’ creation and section 4 on firms’ and aggregate growth. Section 5 explores whether the impact of local financial development on firm’s mark-up and growth differs as a function of the size of the firm, as predicted by theory. Section 6 discusses the relation between our findings and the literature on international financial integration. Conclusions follow.Financial markets are becoming increasingly integrated throughout the world. Does this mean that domestic financial institutions become irrelevant? Our paper suggests not. We show that even in a country (Italy) that has been fully integrated for the last 140 years, local financial development still matters. Therefore, domestic financial institutions are likely to remain important in a financially integrated Europe and, more broadly, in a financially integrated world for time to come.Our evidence also suggests that, as predicted by theory, local financial development is differentially important for large and small firms. Not only does this result support the existence of a causal link between local financial development and real economic variables, but it also raises some questions on the economic effects of financial integration. As Europe and the world are becoming more integrated, large firms will become increasingly uninterested of the conditions of the local financial system, while small firms will continue to rely on it. Hence, depending on the initial size distribution of firms and the minimum threshold to access foreign capital markets, the political support in favor of domestic financial markets might vanish or strengthen as the world becomes more financially integrated. Policy makers working at the European integration should seriously consider this effect, which might explain the persistent underdevelopment of vast areas in Italy 140 years after unification.二、翻译文章区域金融一体化发展问题我们研究区域金融发展差异对金融市场一体化的影响。