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The analysis of the local search efficiency of genetic neural networks and the improvement of algorithm

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4 Author(s)
Shaochun Wen ; Coll. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou, China ; Fei Luo ; Hongqiang Mo ; Ting Lu

Several concepts, such as "locus fitness" and "locus influencing factors", and a coding norm of "maximizing the locus influencing factors" are proposed, based on which the local search efficiency of genetic neural networks is analyzed. To counter the problem that "locus influencing factors" are too small, we modify the algorithm by rising the probabilities of mutation and crossover to improve the optimum seeking performance.

Published in:
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on  (Volume:3 )

Date of Conference: 2002

Page(s):
1789 - 1793 vol.3
Print ISBN:
0-7803-7268-9
INSPEC Accession Number:
7412467
Digital Object Identifier :
10.1109/WCICA.2002.1021390
Product Type:
Conference Publications

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