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Application of an Improved Genetic Algorithm to the Learning of Neural Networks
Yasumasa IKUNO Hiroaki HAWABATA Yoshiaki SHIRAO Masaya HIRATA Toshikuni NAGAHARA Yashio INAGAKI
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 1994/04/25
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Neural Networks
neural network, genetic algorithm, back propagation,
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Recently, the back propagation method, which is one of the algorithms for learning neural networks, has been widely applied to various fields because of its excellent characteristics. But it has drawbacks, for example, slowness of learning speed, the possibility of falling into a local minimum and the necessity of adjusting a learning constant in every application. In this article we propose an algorithm which overcomes some of the drawbacks of the back propagation by using an improved genetic algorithm.