Determination and adaptive alteration of artificial neural network structures by a genetic algorithm with a controlled genotype-phenotype mapping

Junichi Murata, Kei Tanaka, Kotaro Hirasawa

Research output: Contribution to journalConference article

Abstract

A method is proposed for determination and adaptive alteration of artificial neural network (ANN) structures. Not only the weights but also the structure is altered adaptively. From the engineering viewpoint, such an adaptation will be beneficial, for example, for accommodation to faults which requires different structures of the ANN. The salient point of the proposed method is that it can alter the ANN structure by adjusting a single parameter; we do not need to worry about which particular nodes to be removed or where and how many nodes to be added. The method is based on genetic algorithms (GA) which emulate evolution. A fitness function and a coding system of ANN structures on chromosomes are also proposed which are appropriate for optimization of the ANN structures.

Original languageEnglish
Pages (from-to)1690-1695
Number of pages6
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume3
Publication statusPublished - Dec 1 1996
EventProceedings of the 1996 IEEE International Conference on Systems, Man and Cybernetics. Part 3 (of 4) - Beijing, China
Duration: Oct 14 1996Oct 17 1996

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Hardware and Architecture

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