最佳設計
Optimum Design
學期
111-2
學分
3
學分
當期課號
536108
永久課號
ENME30021
開課單位
機械工程學系
授課教師
林聰穎
校區
光復
類別
選修
上課時間表
| 節 | 週二 |
|---|---|
A 18:30–19:20 | 最佳設計 EE210 3 節連堂 |
B 19:30–20:20 | |
C 20:30–21:20 |
* 根據陽明交大上課時間表所列
概述
The purpose of this course is to introduce basic concepts of the optimization theory, and make students to realize how to use this tool during engineering design activities in order to improve the design quality. The most popular application of optimization theory, AI machine learning, will be introduced in final.
先修科目
MATLAB Programming
評分方式
Midterm : 33% Final test : 33% Final reports: 34%
課程大綱
- Introduction to Design
- Optimum design problem formulation
- Grapical optimization
- Optimum design concepts
- Numerical methods for unconstrained & constrained optimum design
- AI machine learning
週次計畫
| 週次 | 主題 |
|---|---|
| 第 1 週 | Overview |
| 第 2 週 | Introduction to Design |
| 第 3 週 | Engineering Math. Review |
| 第 4 週 | Formulation for Optimum Design |
| 第 5 週 | Formulation for Optimum Design |
| 第 6 週 | Graphical Optimization |
| 第 7 週 | Optimum Design Concepts |
| 第 8 週 | Optimum Design Concepts |
| 第 9 週 | Midterm |
| 第 10 週 | Basics for unconstraint Optimum Design |
| 第 11 週 | Numerical Methods for Unconstraint Optimum Design - One Dimensional Search |
| 第 12 週 | Numerical Methods for Unconstraint Optimum Design - Steepest Descent Method, Conjugate Gradient Method, Newton's Method, DFP Method, BFGS Method |
| 第 13 週 | Numerical Methods for Unconstraint Optimum Design - Steepest Descent Method, Conjugate Gradient Method, Newton's Method, DFP Method, BFGS Method |
| 第 14 週 | Numerical Methods for constraint Optimum Design - SLP, SQP |
| 第 15 週 | History of AI |
| 第 16 週 | BP Algorithm |
| 第 17 週 | CNN model |
| 第 18 週 | Final Test |
教科書
Introduction to Optimum Design, J. S. Arora, 4th Ed., 2017.
Office Hours
- 時間
- One hour before and after class
- 聯絡方式
- tsylin0912@hotmail.com