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     Research Journal of Applied Sciences, Engineering and Technology


Optimization Design based on BP Neural Network and GA Method

Bing Wang and Xiaoli Wang
School of Mechanical Engineering, Huaihai Institute of Technology, Lianyungang 222005, China
Research Journal of Applied Sciences, Engineering and Technology  2013  22:4121-4124
http://dx.doi.org/10.19026/rjaset.6.3520  |  © The Author(s) 2013
Received: March 06, 2012  |  Accepted: January 11, 2013  |  Published: December 05, 2013

Abstract

This study puts forward one kind optimization controlling solution method on complicated system. At first modeling using neural network then adopt the real data to structure the neural network model of pertinence, make the parameter to seek to the neural network model excellently by mixing GA finally, thus got intelligence to the complicated system to optimize and control. The method can identify network configuration and network training methods. By adopting the number coding and effectively reducing the network size and the network convergence time, increase the network training speed. The study provides this and optimizes relevant MATLAB procedure which controls the method, so long as adjust a little to the concrete problem, can believe this procedure well the optimization of the complicated system controls the problem in the reality of solving.

Keywords:

GA, neural network, optimization control,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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