J4 ›› 2014, Vol. 27 ›› Issue (1): 68-72.doi: 10.3976/j.issn.1002-4026.2014.01.012

• 论文 • 上一篇    下一篇

数值优化改进的BP神经网络逼近性能对比研究

丁硕,常晓恒,巫庆辉,杨友林   

  1. 渤海大学工学院,辽宁 锦州 121013
  • 收稿日期:2013-07-02 出版日期:2014-02-20 发布日期:2014-02-20
  • 作者简介:丁硕(1979-),男,讲师,研究方向为动态检测、测试信号处理以及虚拟仪器。Email:dingshuo2004@sina.com
  • 基金资助:

    国家自然科学基金(61104071);辽宁省教育厅科学研究一般项目(L2012402)

Comparative study of approximation performance of numerical optimization improved BP neural networks

 DING Shuo, CHANG Xiao-Heng, WU Qing-Hui, YANG You-Lin   

  1. School of Industry, Bohai University, Jinzhou 121013, China
  • Received:2013-07-02 Online:2014-02-20 Published:2014-02-20

摘要:

为了比较不同的数值优化改进的BP神经网络的逼近性能,本文在MATLAB 7.0环境下,建立了三类基于数值优化改进的BP算法,并以非线性函数逼近为例,对7种典型的数值优化改进算法进行网络训练和仿真实验,得出了在不同环境下,每种数值优化差法逼近的可行性。

关键词: 数值优化, BP神经网络, 逼近性能, 对比研究

Abstract:

We address numerical optimization improved BP neural network algorithms to compare their approximation capabilities. We establish three kinds of numerical optimization improved BP algorithms in MATLAB 7.0. Network training and simulation test are then performed for seven typical numerical optimization improved algorithms with nonlinear function approximation as an example. We compare the approximation performance of different numerical optimization in defferent environments.

Key words: numerical optimization, BP neural networks, approximation performance, comparative study

中图分类号: 

  • TP391.9