DocumentCode :
1872472
Title :
Structured learning in recurrent neural network using genetic algorithm with internal copy operator
Author :
Kumagai, Toru ; Wada, Mitsuo ; Mikami, Sadayoshi ; Hashimoto, Ryoichi
Author_Institution :
Nat. Inst. of Biosci. & Human-Technol., Japan
fYear :
1997
fDate :
13-16 Apr 1997
Firstpage :
651
Lastpage :
656
Abstract :
We compose a genetic algorithm that uses an internal copy operator for recurrent neural network learning. The internal copy operator copies one part of a gene to another part of the same gene. We show that the proposed algorithm accelerates learning. We also show that the internal copy operator organizes the structure in the network. The organized structure improves the learning ability and makes it possible to acquire a set of limit cycles easily
Keywords :
genetic algorithms; learning (artificial intelligence); limit cycles; recurrent neural nets; gene copying; genetic algorithm; internal copy operator; learning ability; limit cycles; network structure organization; recurrent neural network; structured learning; Acceleration; Biological neural networks; Data mining; Frequency; Genetic algorithms; Intelligent networks; Limit-cycles; Neural networks; Neurons; Recurrent neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 1997., IEEE International Conference on
Conference_Location :
Indianapolis, IN
Print_ISBN :
0-7803-3949-5
Type :
conf
DOI :
10.1109/ICEC.1997.592395
Filename :
592395
Link To Document :
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