Evolutionary algorithms for training neural networks

被引：0
|
作者：
Mohan, Chilukuri K. [1 ]
机构：
[1] Syracuse Univ, Dept Elect Engn & Comp Sci, Syracuse, NY 13244 USA
来源：
MODELING AND SIMULATION FOR MILITARY APPLICATIONS | 2006年 / 6228卷
关键词：
neural networks; evolutionary algorithms; parameter learning; model learning; ensemble models; optimization;
D O I：
10.1117/12.670263
中图分类号：
V [航空、航天];
学科分类号：
08 ; 0825 ;
摘要：
This paper surveys the various approaches used to apply evolutionary algorithms to develop artificial neural networks that solve pattern recognition, classification, and other tasks. These approaches are classified into four groups, each addressing one aspect of an artificial neural network: (a) evolving connection weights; (b) evolving neural architectures; (c) evolving an ensemble of networks; and (d) evolving node functions. Hybrid approaches are also discussed.
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收藏
页数：9
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