.png){kind=icon}
返回
.png){kind=icon}
.png){kind=icon}
摘要
En 中文
The filled function method (FFM) is an approach to find the global minimizer of multi-modal functions. The numerical applicability of conventional filled functions is limited as they are defined on either exponential or logarithmic terms. This paper proposes a new filled function that does not have such disadvantages. An algorithm is presented according to the theoretical analysis. A computer program is designed, implemented, and tested. Numerical experiments on typical testing functions show that the new approach is superior to the conventional one. The result of optimization design for an electrical machine is also reported.
Keyword:
filled function method
global optimization
mathematical programming
minimization
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
C
IF:
4.3
论文数:
6.5K
被引数:
1.8W
机构
暂无机构信息
引用论文
Maize genotype susceptibility to Rhizoctonia solani and its effect on sugar beet crop rotations.png)
.png){kind=icon}
PREAI
.png){kind=icon}
分享.png){kind=icon}
收藏Surface Plasmon Resonance of Ag Nanoparticles Embedded in Partially Oxidized Amorphous Si Matrix
PREAI
分享收藏分享收藏
查看更多内容