The analysis of convergence of hybrid algorithm based on neural network and genetic algorithm

被引：0
|
作者：
Pan, MQ [1 ]
He, GP [1 ]
机构：
[1] Shan Dong Univ Sci & Technol, Coll Info Sci & Engn, QingDao 266510, Peoples R China
来源：
PROCEEDINGS OF THE 2005 INTERNATIONAL CONFERENCE ON NEURAL NETWORKS AND BRAIN, VOLS 1-3 | 2005年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper analyzes the advantages and disadvantages of GA and BP algorithms, and presents the iteration of hybrid algorithm based on both algorithms. The hybrid algorithm incorporates the stronger global search of GA into the stronger local search of BP, and can search out the global optimum faster than each algorithm. At last, the hybrid algorithm is proved converge to the global optimum with the probability of 1.
引用
收藏
页码：232 / 235
页数：4
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