99年第1學期-4441 數量分析方法 課程資訊

評分方式

評分項目	配分比例	說明
期中報告	50
期末報告	50

教育目標

Part of this course introduces the mathematical theory of probability and stochastic processes. Subjects include Markov chains, the Poisson process; continuous-time stochastic processes; 介紹討論數量分析方法之概念，培養學生於數量分析中最佳化方法之基本概念。

課程概述

介紹討論數量分析方法之概念，培養學生於數量分析中最佳化方法之基本概念。 This part of the course is one of the 4 consecutive topics. This one is focused on the AI-Based search methods. The basic concepts and the major methods and models will be delivered in the lectures.

基本資料

必選課，學分數：3-0
上課時間：五/2,3,4[會議室]
修課班級：工工博1
修課年級：年級以上
選課備註：801

參考書目

第一部分授課教師：翁紹仁老師
1. Banks, J. and John S. Carson, II, Discrete-Event System Simulation, Prentice-Hall, 1984.
2. Winston, W. L., Operations Research: Applications and Algorithms, 2nd Ed., Duxbury Press, Belmont, California, 1991

第二部分授課教師：張炳騰老師
1. S. S. Rao, ENGINEERING OPTIMIZATION: THEORY AND PRACTICE, 3rd Edition, John Wiley & Sons, 1996.
2. G. N. Vanderplaats, NUMERICAL OPTIMIZATION TECHNIQUES FOR ENGINEERING DESIGN WITH APPLICATIONS, McGraw-Hill, 1994.
3. M. S. Bazaraa, H. D. Sherali and C. M. Shetty, NONLINEAR PROGRAMMING: THEORY AND ALGORITHMS, 2nd Edition, John Wiley & Sons, 1993.

第三部分授課教師：彭 泉老師
1. Goodman Roe, Introduction to Stochastic Models: Second Edition, 2006, Dover Publications, originally published by The Benjamin/Cummings Publishing Company, Inc., 1988, ISBN: 0486450376

第四部分授課教師：王偉華老師
1. Haykin, Simon, Neural Networks. (2nd edi )
2. Cristianini, Nello, An Introduction to Support Vector Machines.
3. Neapolitan, Richard E., Learning Bayesian Networks, Prentice Hall, 2004