Modification of Steepest Descent Method for Solving Unconstrained Optimization
The Classical steepest descent (SD) method is known as one of the earliest and the best method to minimize a function. Even though the convergence rate is quite slow, but its simplicity has made it one of the easiest methods to be used and applied especially in the form of computer codes.
Saved in:
主要作者: | Zubai'dah Binti Zainal Abidin |
---|---|
格式: | Thesis |
语言: | English |
出版: |
Universiti Malaysia Terengganu
2023
|
主题: | |
在线阅读: | http://umt-ir.umt.edu.my:8080/handle/123456789/17622 |
标签: |
添加标签
没有标签, 成为第一个标记此记录!
|
相似书籍
-
A new multi-step gradient method for optimization problem
由: Mahboubeh, Farid, et al.
出版: (2010) -
The investigation of gradient method namely Steepest Descent and extending of Barzilai Borwein for solving unconstrained optimization problem / Nur Intan Syahirah Ismail & Nur Atikah Aziz
由: Ismail, Nur Intan Syahirah, et al.
出版: (2019) -
Scaled memoryless BFGS preconditioned steepest descent method for very large-scale unconstrained optimization
由: Leong, Wah June, et al.
出版: (2009) -
Preconditioning Subspace Quasi-Newton Method for Large Scale Unconstrained Optimization
由: Sim, Hong Sen
出版: (2011) -
Energy Management in Integrated Microgrids: An Optimal Schedule Controller Utilizing Gradient Descent Algorithm
由: Abdolrasol M.G.M., et al.
出版: (2024)