人工智能与知识工程【英文】
课文翻译 整理版222
Unit 1Artificial intelligence，computer programs. 人工智能是制造智能机器的科学与工程，特别是智能化的计算机程序。
It is related，observable.这与使用计算机来理解人类智能的类似任务有关，但是人工智能不需要把它局限在生物可观察的方法上。
In this unit,research .在这个单元，两个章节提出了人工智能研究的概况。
Text A briefly，so on.文章A简要介绍了人工智能的定义，人工智能的系统的几种体系结构、基本功能以及程序等等。
Text B Turing’s Test.文章B解释特定地区研究人工智能的自然语言处理包括定义和传说中的图灵测试。
Unit 2Telecommunication , social advancement.电信网络已成为战略组成的全球基础设施来支持经济的发展，科学发现，教育机会和社会进步。
They are rapidly, wireless facilities.他们迅速发展为支持集成的多媒体服务。
包括语言，数据，在基于光纤的有线和无线设备，和基于蜂窝的全运动视频图像。
Text A provides ，and services.文章A提供了一个全面的内容概述全球移动通信系统。
包括GSM，基本概念的规范，网络和服务。
Text B introduces，cell phone.文章B介绍了现代电信的一种新发明，即多功能手机。
Some topics ，in detail.关于它的基本制造过程中的一些主题，目标受众和潜在的分布都进行了详细的讨论。
Unit 3Internet seems ，in this unit . 互联网似乎已成为现代生活不可或缺的一部分。
但它既有优点也有缺点，可能在这一单元的第二段中看到。
Text A points ，who wants it . 文章指出，人们可以通过互联网获取大量个人信息，然后告诉我们想要的信息。
人工智能英文课件
Supervised learning is a type of machine learning where the algorithm is provided with labeled training data The goal is to learn a function that maps input data to desired outputs based on the provided labels Common examples include classification and regression tasks
Deep learning is a type of machine learning that uses neural networks with multiple layers of hidden units to learn complex patterns and representations from data It is based on biomimetic neural networks and self-organizing mapping networks.
Machine translation is the process of automatically translating text or speech from one language to another using computer algorithms and language data banks This technology has identified the need for human translators in many scenarios
Some challenges associated with deep learning include the requirement for large amounts of labeled data, the complexity of explaining the learned patterns or representations, and the potential for overflow or poor generalization to unseen data
人工智能 专业英语
Develo pment
Achiev ement
Applic ations
2016/5/18
Present
Neural Networks 1986
Knowledge Engineering 1977
Difficulties 1966
Birth of AI 1956 Turing Test 1936
SumAchiev ement
Applic ations
2016/5/18
• The main areas • General machine Natural Computer intelligence, conversationl language vision learning behavior ,data-mining, AI • Driverless cars, robot Pattern Expert recognition soccer and games system
2016/5/18
Devel opme nt
Achiev ement
What is AI? Applica tion
2016/5/18
2016/5/18
Artificial Intelligence (AI) is the
intelligence of machines and the
branch of computer science that aims to create it. Definition in AI textbook :”the study and design of intelligent agents”
Summa ry
Develo pment
Achiev ement
大学各专业名称英文翻译(一)——工学_ENGINEERING
大学各专业名称英文翻译（一）——工学ENGINEERING课程中文名称课程英文名称高等数理方法Advanced Mathematical Method弹塑性力学Elastic-Plastic Mechanics板壳理论Theory of Plate and Shell高等工程力学Advanced Engineering Mechanics板壳非线性力学Nonlinear Mechanics of Plate and Shell复合材料结构力学Structural Mechanics of Composite Material弹性元件的理论及设计Theory and Design of Elastic Element非线性振动Nonlinear Vibration高等土力学Advanced Soil Mechanics分析力学Analytic Mechanics随机振动Random Vibration数值分析Numerical Analysis基础工程计算与分析Calculation and Analysis of Founda tion Engineering结构动力学Structural Dynamics实验力学Laboratory Mechanics损伤与断裂Damage and Fracture小波分析Wavelet Analysis有限元与边界元分析方法Analytical Method of Finite Element and Boundary Element最优化设计方法Optimal Design Method弹性力学Elastic Mechanics高层建筑基础Tall Building Foundation动力学Dynanics土的本构关系Soil Constitutive Relation数学建模Mathematical Modeling现代通信理论与技术Emerging Communications Theory and Technology数字信号处理Digital Signal Processing网络理论与多媒体技术Multi-media and Network Technology医用电子学Electronics for Medicine计算微电子学Computational Microelectronics集成电路材料和系统电子学Material and System Electronics for In tegrated Circuits网络集成与大型数据库Computer Network Integrating Technology and Large scale Database 现代数字系统Modern Digital System微机应用系统设计Microcomputer Application Design计算机网络新技术Modern Computer Network Technologies网络信息系统Network Information System图像传输与处理Image Transmission and Processing图像编码理论Theory of Image Coding遥感技术Remote Sensing Techniques虚拟仪器系统设计Design of Virtual Instrument System生物医学信号处理技术Signal Processing for Biology and Medicine光纤光学Fiber OpticsVLSI的EDA技术EDA Techniques for VLSI电子系统的ASIC技术ASIC Design TechnologiesVLSI技术与检测方法VLSI Techniques & Its Examination专题阅读或专题研究The Special Subject Study信息论Information Theory半导体物理学Semiconductor Physics通信原理Principle of Communication现代数理逻辑Modern Mathematical Logic算法分析与设计Analysis and Design of Algorithms高级计算机网络Advanced Computer Networks高级软件工程Advanced Software Engineering数字图像处理Digital Image Processing知识工程原理Principles of Knowledge Engineering面向对象程序设计Object-Oriented Programming形式语言与自动机Formal Languages and Automata人工智能程序设计Artificial Intelligence Programming软件质量与测试Software Quality and Testing大型数据库原理与高级开发技术Principles of Large-Scale Data-Bas e and Advanced Development Technology自然智能与人工智能Natural Intelligence and Artificial Intelligence Unix操作系统分析Analysis of Unix System计算机图形学Computer GraphicsInternet与Intranet技术Internet and Intranet Technology多媒体技术Multimedia Technology数据仓库技术与联机分析处理Data Warehouse and OLAP程序设计方法学Methodology of Programming计算机信息保密与安全Secrecy and Security of Computer Information电子商务Electronic Commerce分布式系统与分布式处理Distributed Systems and Distributed Processing并行处理与并行程序设计Parallel Processing and Parallel Programming模糊信息处理技术Fuzzy Information Processing Technology人工神经网络及应用Artificial Intelligence and Its Applications Unix编程环境Unix Programming Environment计算机视觉Computer Vision高级管理信息系统Advanced Management Information Systems信息系统综合集成理论及方法Theory and Methodology of Information n System Integration计算机科学研究新进展Advances in Computer Science离散数学Discrete Mathematics操作系统Operating System数据库原理Principles of Database编译原理Principles of Compiler程序设计语言Programming Language数据结构Data Structure计算机科学中的逻辑学Logic in Computer Science面向对象系统分析与设计Object-Oriented System Analysis and Design高等数值分析Advanced Numeric Analysis人工智能技术Artificial Intelligence Technology软计算理论及应用Theory and Application of Soft-Computing逻辑程序设计与专家系统Logic Programming and Expert Systems模式识别Pattern Recognition软件测试技术Software Testing Technology高级计算机网络与集成技术Advanced Computer Networks and Integration Technology 语音信号处理Speech Signal Processing系统分析与软件工具System Analysis and Software Tools计算机仿真Computer Simulation计算机控制Computer Control图像通信技术Image Communication Technology人工神经网络及应用Artificial Intelligence and Its Applications计算机技术研究新进展Advances in Computer Technology环境生物学Environmental Biology水环境生态学模型Models of Water Quality环境化学Environmental Chemistry环境生物技术Environmental Biotechnology水域生态学Aquatic Ecology环境工程Environmental Engineering环境科学研究方法Study Methodology of Environmental Science藻类生理生态学Ecological Physiology in Algae水生动物生理生态学Physiological Ecology of Aquatic Animal专业文献综述Review on Special Information废水处理与回用Sewage Disposal and Re-use生物医学材料学及实验Biomaterials and Experiments现代测试分析Modern Testing Technology and Methods生物材料结构与性能Structures and Properties of Biomaterials计算机基础Computer Basis医学信息学Medical Informatics计算机汇编语言Computer Assembly Language学科前沿讲座Lectures on Frontiers of the Discipline组织工程学Tissue Engineering生物医学工程概论Introduction to Biomedical Engineering高等生物化学Advanced Biochemistry光学与统计物理Optics and Statistical Physics图像分析Image Treatment数据处理分析与建模Data Analysis and Constituting Model高级数据库Advanced Database计算机网络Computer Network多媒体技术Technology of Multimedia软件工程Software Engineering药物化学Pharmaceutical Chemistry功能高分子Functional Polymer InternetIntranet程序设计方法学Methods of Programming InternetIntranet高分子化学与物理Polymeric Chemistry and Physics医学电子学Medical Electronics现代仪器分析Modern Instrumental Analysis仪器分析实验Instrumental Analysis Experiment食品添加剂Food Additives Technology高级食品化学Advanced Food Chemistry食品酶学Food Enzymology现代科学前沿选论Literature on Advances of Modern Science波谱学Spectroscopy波谱学实验Spectroscopic Experiment食品贮运与包装Food Packaging液晶化学Liquid Crystal Chemistry高等有机化学Advanced organic Chemistry功能性食品Function Foods食品营养与卫生学Food Nutrition and Hygiene食品生物技术Food Biotechnology食品研究与开发Food Research and Development有机合成化学Synthetic organic Chemistry食品分离技术Food Separation Technique精细化工装备Refinery Chemical Equipment食品包装原理Principle of Food Packaging表面活性剂化学及应用Chemistry and Application of Surfactant天然产物研究与开发Research and Development of Natural Products 食品工艺学Food Technology生物化学Biochemistry食品分析Food Analysis食品机械与设备Food Machinery and Equipment。
智能科学与技术专业英语
智能科学与技术专业英语一、单词1. Artificial Intelligence (AI)- 英语释义：The theory and development ofputer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision - making, and translation between languages.- 用法：“Artificial Intelligence” is often abbreviated as “AI” and can be used as a subject or in phrases like “AI technology” or “the field of AI”.- 双语例句：- Artificial Intelligence has made great progress in recent years. (近年来，人工智能取得了巨大的进展。
)- Manypanies are investing heavily in artificial intelligence research. (许多公司正在大力投资人工智能研究。
)2. Algorithm- 英语释义：A set ofputational steps and rules for performing a specific task.- 用法：Can be used as a countable noun, e.g. “T his algorithm is very efficient.”- 双语例句：- The new algorithm can solve the problem much faster. (新算法可以更快地解决这个问题。
人工智能英语作文必备知识点
人工智能英语作文必备知识点Title: The Evolution and Impact of Artificial Intelligence.Artificial intelligence (AI) has emerged as a pivotal technology in our modern world, revolutionizing the way we live, work, and interact. Its reach is vast and ever-expanding, touching every aspect of human life from healthcare to entertainment, transportation to education. In this essay, we delve into the evolution of AI, its current applications, and the potential impact it holds for the future.Evolution of AI.The journey of AI began in the early days of computing, when machines were programmed to perform specific tasks. This era was marked by the development of logic programs and expert systems that模仿 human expertise in narrow domains. However, it was the advent of machine learning inthe 1980s and 1990s that truly marked a turning point. Machine learning enabled computers to learn from data and make predictions without being explicitly programmed. This approach revolutionized AI, leading to the emergence of systems that could adapt and improve over time.The past decade has seen a further leap in AI technology with the advent of deep learning. Deep learning algorithms, powered by vast amounts of data and powerful computing resources, have enabled machines to achieve human-like performance in tasks such as image recognition, speech recognition, and natural language processing. This has led to the creation of intelligent assistants, autonomous vehicles, and a range of other cutting-edge applications.Current Applications of AI.AI is now pervasive in our daily lives, shaping the way we interact with technology and the world at large. Here are some of the key areas where AI is making significant impacts:1. Healthcare: AI is revolutionizing healthcare by enabling more accurate diagnoses, personalized treatments, and efficient patient management. Machine learning algorithms can analyze vast amounts of medical data to identify patterns and predict outcomes, assisting doctorsin making informed decisions. AI-powered robots are also being used in surgical procedures, improving precision and reducing human error.2. Education: AI is transforming the education sector by personalizing learning experiences and providing adaptive learning paths for students. Intelligent tutoring systems can identify student strengths and weaknesses and provide targeted feedback and resources. AI-based tools are also being used to analyze student performance data, informing teaching methods and curriculum design.3. Transportation: Autonomous vehicles are one of the most exciting applications of AI. By using a combination of sensors, cameras, and machine learning algorithms, autonomous vehicles can navigate roads safely andefficiently, reducing accidents and traffic congestion. AIis also being used in other areas of transportation, suchas air traffic control and logistics management, improving efficiency and reducing waste.4. Entertainment: AI is revolutionizing the entertainment industry by enabling more interactive and personalized experiences. Recommender systems powered by AI algorithms analyze user preferences and behavior to suggest content that matches their interests. AI is also being used in gaming to create more realistic and engaging environments, as well as in music and art creation,enabling artists to explore new styles and techniques.Future Impact of AI.The potential impact of AI on society and the economyis immense. As AI systems become more intelligent and autonomous, they will likely play an increasingly critical role in various sectors, including manufacturing, finance, and even government. This will lead to increased efficiency, productivity, and innovation, but also present newchallenges and ethical considerations.One of the key challenges is the displacement of jobs due to automation. As AI systems become capable of performing tasks that were traditionally done by humans, there will be a need to retrain workers and create new job opportunities. It will be crucial for governments and educational institutions to invest in skills development and lifelong learning programs to prepare the workforce for the future.Another challenge is the ethical implications of AI. As AI systems become more autonomous, there will be increasing concerns about privacy, security, and accountability. It will be essential to develop robust frameworks and regulations to ensure that AI systems are designed and used ethically, respecting human rights and values.Despite these challenges, the potential benefits of AI are vast. AI systems have the potential to solve complex problems that have previously been intractable, such as climate change and global poverty. By harnessing the powerof data and machine learning, we can make informed decisions and create more effective solutions to address these issues.In conclusion, AI is poised to transform our world in profound ways. It has the potential to bring about remarkable improvements in areas such as healthcare, education, transportation, and entertainment. However, we must also be mindful of the challenges and ethical implications that come with this technology. By investing in skills development, ethical frameworks, and innovative policies, we can harness the power of AI to create a better future for all.。
人工智能概论中英文术语对照表
人工智能概论中英文术语对照表动作action专家系统Expert system人工智能语言AI language祖先过滤形策略ancestry-filtered form strategy与节点AND node与或图AND/OR graph与或树AND/OR tree回答语句answer statement人工智能artificial intelligence,AI原子公式atomic formula自动定理证明automatic theorem provingB规则B-rule倒退值backed-up value回溯backtracking盲目搜索，无信息搜索blind search宽度优先搜索breadth-first search子句clause组合爆炸combinatorial explosion冲突解决conflict resolution合取式conjunct合取conjunction合取范式conjunctive normal form连词，连接词connective一致解图consistant solution graph控制策略control strategy费用cost演绎deduction深度优先搜索depth-first search推导表，引导图derivation graph差别difference有向图directed graph析取式disjunct析取disjunction谓词演算辖域domain in predicate calculus论域，文字域domain of discourse搜索算法的效率efficiency of search algorithm空子句empty clause等价equivalence估计费用estimated cost估值函数evaluation function存在量词existential quantifier扩展节点expending node节点的扩展expansion of nodeF规则F-rule事实fact一阶谓词演算first order predicate calculus 博弈game图graph图表示法graph notation图搜索graph search图搜索控制策略graph-search control strategy 启发函数heuristic function启发信息heuristic information启发搜索heuristic search蕴涵，蕴涵式implication推理inference智能intelligence解释器interpreter知识knowledge知识获取knowledge acquisition全局数据库Global database知识库knowledge base知识工程knowledge engineering学习learning启发式搜索Heuristic search线形输入形策略linear-input form strategy文字literal逻辑logic逻辑连词logic connective逻辑推理logic reasoning匹配match模式匹配match pattern母式matrix最一般合一者most general unifierNP完全问题NP-complete problem算符、算子、操作符operator最优解树optimal solution tree有序搜索ordered search谓词predicate谓词演算predicate calculus谓词逻辑predicate logic前缀prefix本原问题primitive problem问题归约problem-reduction问题求解problem solving产生式production产生式规则production rule量词quantifier推理reasoning正向推理forward reasoning逆向推理backward reasoning推理机reasoning machine归约reduction反演refutation反演树refutation tree归结resolution归结原理resolution principle归结反演resolution refutation归结式resolvent可满足性satisfiability模式识别Pattern recognition量词辖域scope of quantifier搜索search, searching搜索算法searching algorithm搜索图searching graph搜索策略searching strategy搜索树searching tree句子sentence解图solution graph解树solution tree可解节点solvable node可解标示过程solvable labeling procedure 状态state状态空间state space代换例substitution instance代换substitution重言式tautology项term定理证明theorem-proving不确定性uncertainty合一unifier最一般合一most general unifier全称量词universal quantifier不可满足集unsatisfiable set不可解标示过程unsolvable-labeling procedure 不可解节点unsolvable node永真式validity合适公式、合式公式well-formed formula (wff)谓词演算公式wffs of predicate calculus人工神经网络artificial neural network遗传算法genetic algorithm机器学习machine learning。
人工智能英语 Unit 2 Machine Learning
Lead-in
Part I
Part I
Task 1 The following are common terms used in machine learning. Please match them with their Chinese translation. Look them up in a dictionary if necessary.
Part II
Types of machine learning Depending upon the nature of the data and the desired outcome, machine learning are divided into 4 primary types. Supervised machine learning Addressing datasets with labels or structure，data acts as a teacher and “trains” the machine, increasing in its ability to make a prediction or decision.
Part I
Task 2 Listen to the short passage and choose the proper words to fill in the blanks.
In the past, humans built algorithmic bots by giving them instructions that humans could 1________. If this, than that. But many problems are just too big and complex for a human to write simple instructions for. There are countless videos on Tiktok, which ones should the users see as 2______________? There’s a a huge amount of financial transactions a second, which ones are fraudulent? For this beautiful dress, what is the 3 ________ price this user will pay right now?
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N. Kasabov, Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering, MIT Press, 1996
Heuristic Problem Solving
Figure 1.1 Heuristics as means of obtaining restricted projections from the domain space D into the solution space S.
N. Kasabov, Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering, MIT Press, 1996
Heuristic Problem Solving (cont)
Figure 1.2: (a) Ill-informed and (b) well-informed heuristics. They are represented as `patches' in the problem space. The patches have different forms (usually quadrilateral) depending on the way of representing the heuristics in a computer program.
N. Kasabov, Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering, MIT Press, 1996
Heuristic Problem Solving (cont)
Figure 1.3: The problem knowledge maps the domain space into the solution space and approximates the objective (goal) function: (a) a general case; (b) two dimensional case.
N. Kasabov, Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering, MIT Press, 1996
Introduction to the AI Paradigms (cont)
AI directions: developing methods and systems for solving AI problems without following the way the humans do (expert systems) developing methods and systems for solving AI problems through modelling the human way of thinking, or the way the brain works (neural networks) AI paradigms: symbolic or sub-symbolic (connectionist)
N. Kasabov, Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering, MIT Press, 1996
Introduction to the AI Paradigms
AI objectives: to develop methods and systems for solving problems, usually solved through intellectual activity of humans, eg. image recognition language and speech processing; planning, prediction, etc., thus enhancing the computer information systems to improve our understanding on how the human brain works
N. Kasabov, Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering, MIT Press, 1996
Genetic Algorithms and Evolutionary Programming
An Introduction to Artificial Intelligence and Knowledge Engineering
N. Kasabov, Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering, MIT Press, 1996
Sub-topics:
Introduction to the AI paradigms (1.1; pp. 1-3) Heuristic problem solving (1.2; pp. 3-9) Genetic algorithms and evolutionary programming (1.2.3; pp. 9-14) Expert systems (1.3.1; pp. 14-15) Fuzzy systems (1.3.2; pp. 15-17) Neural networks (1.3.3; pp. 17-19) Hybrid systems (1.3.4; 1.9, pp. 65-68)