Study On the Radical Basis Function Neural Network Based On Niche Genetic Algorithms

DOI

10.2991/isaeece-16.2016.33How to use a DOI?

Keywords

RBF, niche genetic algorithms, optimization, global search

Abstract

When building a radial basis function (RBF) neural network with the traditional clustering method , the expression of the network is often affected by the distribution of training samples.The ability of learning and generalization are hard to achieve the optimum.In this paper, it presents to through replacing the traditional clustering algorithms with the niche genetic algorithms for solving the matters above. Through tests, the results showed that the new RBF neural network built by niche genetic algorithms(NGA) performed better than the traditional one.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhaohu Deng
PY  - 2016/04
DA  - 2016/04
TI  - Study On the Radical Basis Function Neural Network Based On Niche Genetic Algorithms
BT  - Proceedings of the 2016 International Symposium on Advances in Electrical, Electronics and Computer Engineering
PB  - Atlantis Press
SP  - 161
EP  - 164
SN  - 2352-5401
UR  - https://doi.org/10.2991/isaeece-16.2016.33
DO  - 10.2991/isaeece-16.2016.33
ID  - Deng2016/04
ER  -