Research on the learning algorithm of BP neural networks embedded in evolution strategies - 文章详情页

作者：

Jiang, Weijin (Jiang, Weijin.) | Zhang, Xiaoqi (Zhang, Xiaoqi.) | Zhang, Changfan (Zhang, Changfan.) | Xu, Yusheng (Xu, Yusheng.) | Sun, Xingming (Sun, Xingming.)

收录：

EI Scopus

摘要：

Combining　the　BP　algorithm　and　evolution　algorithm,　the　gradient-BP　algorithm　(EBP)　was　proposed.　Because　BP　algorithm　used　the　idea　of　gradient　descent,　it　was　unavoidable　that　local　minimalism　unperfected　exists.　Evolution　algorithm　was　a　technique　that　simulates　the　evolution　of　animal.　We　introduced　evolution　algorithm　into　BP　algorithm　and　it　formed　an　evolution-BP　algorithm.　EBP　algorithm　absorbed　nonlinear　information　of　the　error　function,　and　it　didn＇t　depend　on　the　gradient　information　of　target　function.　It　not　just　improves　the　speed　of　local　constringency,　but　also　has　the　ability　of　global　constringency.　It　avoids　the　possibility　of　local　minimalism,　and　improves　model＇　precise　and　the　speed　of　calculate.

关键词：

Evolutionary algorithms Error analysis Mathematical models Nonlinear systems Neural networks Computer simulation

作者机构：

[ 1 ] [Jiang, Weijin]Department of Computer, Zhuzhou Institute of Technology, Zhuzhou 412008, China
[ 2 ] [Zhang, Xiaoqi]Department of Computer, Zhuzhou Institute of Technology, Zhuzhou 412008, China
[ 3 ] [Zhang, Changfan]Department of Computer, Zhuzhou Institute of Technology, Zhuzhou 412008, China
[ 4 ] [Xu, Yusheng]Coll. of Mech. Eng./Appl. Electron., Beijing University of Technology, Beijing 100022, China
[ 5 ] [Sun, Xingming]Department of Computer, Zhuzhou Institute of Technology, Zhuzhou 412008, China

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jwj3666@163.com

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