Binary Self-Organizing Map with Modified Updating Rule and Its Application to Reproduction of Genetic Algorithm

Ryosuke KUBOTA  Keiichi HORIO  Takeshi YAMAKAWA  

IEICE TRANSACTIONS on Information and Systems   Vol.E90-D   No.1   pp.382-383
Publication Date: 2007/01/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Biocybernetics, Neurocomputing
genetic algorithm,  self-organizing map,  reproduction,  updating rule,  

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In this paper, we propose a modified reproduction strategy of a Genetic Algorithm (GA) utilizing a Self-Organizing Map (SOM) with a novel updating rule of binary weight vectors based on a significance of elements of inputs. In this rule, an updating order of elements is decided by considering fitness values of individuals in a population. The SOM with the proposed updating rule can realize an effective reproduction.