Research on Optimization Model of Neural Network Based on Genetic Algorithm

DOI

10.2991/iccse-15.2015.12How to use a DOI?

Keywords

Artificial Neural Network; BP Networks; Genetic Algorithms; Optimization

Abstract

BP neural network is a multilayer feed-forward network for training according to the error back-propagation algorithm , its main advantage is the strong non-linear mapping ability , but the training of BP neural network is easy to fall into local minima, and slow convergence speed. This paper makes use of the good global search ability of genetic algorithm , for training the connection weights and thresholds of BP neural network, establishment of GA-BP model, effectively compensate slow convergence speed, easy fall into local minimum shortcomings for BP neural network. Through example analysis, verification of the global optimization capability of GA optimization BP neural network has been greatly improved compared with the pure BP neural network model .

Copyright

© 2015, 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  - Ping Wang
AU  - Bin Yang
PY  - 2015/07
DA  - 2015/07
TI  - Research on Optimization Model of Neural Network Based on Genetic Algorithm
BT  - Proceedings of the 2015 International Conference on Computational Science and Engineering
PB  - Atlantis Press
SP  - 60
EP  - 63
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccse-15.2015.12
DO  - 10.2991/iccse-15.2015.12
ID  - Wang2015/07
ER  -