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首页 数学建模方法与分析txt,chm,pdf,epub,mobi下载作者:米尔斯切特 出版社: 机械工业 出版年: 2009-1 页数: 335 定价: 49.00元 丛书: 经典原版书库 ISBN: 9787111253648 内容简介 · · · · · ·《数学建模方法与分析(英文版·第3版)》提出了一种通用的数学建模方法——五步方法,帮助读者迅速掌握数学建模的真谛。作者以引人入胜的方式描述了数学模型的3个主要领域：最优化、动力系统和随机过程。《数学建模方法与分析(英文版·第3版)》以实用的方法解决各式各样的现实问题,包括空间飞船的对接、传染病的增长率和野生生物的管理等。此外,《数学建模方法与分析(英文版·第3版)》根据需要详细介绍了解决问题所需要的数学知识。 作者简介 · · · · · ·Mark M.Meerschaert美国密歇根州立大学概率统计系主任,内华达大学物理系教授。他曾在密歇根大学、英格兰学院、新西兰达尼丁Otago大学执教。讲授过数学建模、概率、统计学、运筹学、偏微分方程、地下水及地表水水文学与统计物理学课程。他当前的研究方向包括无限方差概率模型的极限定理和参数估计、金融数学中的厚尾模型、用厚尾模型及周期协方差结构建模河水流、异常扩散、连续时间随机流动、分数次导数和分数次偏微分方程、地下水流及运输。 目录 · · · · · ·PrefaceⅠ OPTIMIZATION MODELS1 ONE VARIABLE OPTIMIZATION 1.1 The Five-Step Method 1.2 Sensitivity Analysis 1.3 Sensitivity and Robustness 1.4 Exercises2 MULTIVARIABLE OPTIMIZATION 2.1 Unconstrained Optimization 2.2 Lagrange Multipliers 2.3 Sensitivity Analysis and Shadow Prices 2.4 Exercises3 COMPUTATIONAL METHODS FOR OPTIMIZATION 3.1 One Variable Optimization 3.2 Multivariable Optimization 3.3 Linear Programming 3.4 Discrete Optimization 3.5 ExercisesⅡ DYNAMIC MODELS4 INTRODUCTION TO DYNAMIC MODELS 4.1 Steady State Analysis 4.2 Dynamical Systems 4.3 Discrete Time Dynamical Systems 4.4 Exercises5 ANALYSIS OF DYNAMIC MODELS 5.1 Eigenvalue Methods 5.2 Eigenvalue Methods for Discrete Systems 5.3 Phase Portraits 5.4 Exercises6 SIMULATION OF DYNAMIC MODELS 6.1 Introduction to Simulation 6.2 Continuous-Time Models 6.3 The Euler Method 6.4 Chaos and Fractals 6.5 ExercisesⅢ PROBABILITY MODELS7 INTRODUCTION TO PROBABILITY MODELS 7.1 Discrete Probability Models 7.2 Continuous Probability Models 7.3 Introduction to Statistics 7.4 Diffusion 7.5 Exercises8 STOCHASTIC MODELS 8.1 Markov Chains 8.2 Markov Processes 8.3 Linear Regression 8.4 Time Series 8.5 Exercises9 SIMULATION OF PROBABILITY MODELS 9.1 Monte Carlo Simulation 9.2 The Markov Property 9.3 Analytic Simulation 9.4 ExercisesAfterwordIndexPrefaceⅠ OPTIMIZATION MODELS1 ONE VARIABLE OPTIMIZATION 1.1 The Five-Step Method 1.2 Sensitivity Analysis 1.3 Sensitivity and Robustness 1.4 Exercises2 MULTIVARIABLE OPTIMIZATION 2.1 Unconstrained Optimization 2.2 Lagrange Multipliers 2.3 Sensitivity Analysis and Shadow Prices 2.4 Exercises3 COMPUTATIONAL METHODS FOR OPTIMIZATION 3.1 One Variable Optimization 3.2 Multivariable Optimization 3.3 Linear Programming 3.4 Discrete Optimization 3.5 ExercisesⅡ DYNAMIC MODELS4 INTRODUCTION TO DYNAMIC MODELS 4.1 Steady State Analysis 4.2 Dynamical Systems 4.3 Discrete Time Dynamical Systems 4.4 Exercises5 ANALYSIS OF DYNAMIC MODELS 5.1 Eigenvalue Methods 5.2 Eigenvalue Methods for Discrete Systems 5.3 Phase Portraits 5.4 Exercises6 SIMULATION OF DYNAMIC MODELS 6.1 Introduction to Simulation 6.2 Continuous-Time Models 6.3 The Euler Method 6.4 Chaos and Fractals 6.5 ExercisesⅢ PROBABILITY MODELS7 INTRODUCTION TO PROBABILITY MODELS 7.1 Discrete Probability Models 7.2 Continuous Probability Models 7.3 Introduction to Statistics 7.4 Diffusion 7.5 Exercises8 STOCHASTIC MODELS 8.1 Markov Chains 8.2 Markov Processes 8.3 Linear Regression 8.4 Time Series 8.5 Exercises9 SIMULATION OF PROBABILITY MODELS 9.1 Monte Carlo Simulation 9.2 The Markov Property 9.3 Analytic Simulation 9.4 ExercisesAfterwordIndex · · · · · · () |
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作者： 风封秋
讲的特别好
很多历史的细节。
还没有看完
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