| 数值优化改进的BP神经网络逼近性能对比研究 |
| |
| 引用本文： | 丁硕,常晓恒,巫庆辉,杨友林.数值优化改进的BP神经网络逼近性能对比研究[J].山东科学,2014,27(1):68-72. |
| |
| 作者姓名： | 丁硕 常晓恒 巫庆辉 杨友林 |
| |
| 作者单位： | 渤海大学工学院，辽宁 锦州 121013 |
| |
| 基金项目： | 国家自然科学基金（61104071）;辽宁省教育厅科学研究一般项目（L2012402） |
| |
| 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 |
| 收稿时间： | 2013-07-02 |
Comparative study of approximation performance of numerical optimization improved BP neural networks |
| |
| DING Shuo,CHANG Xiao-heng,WU Qing-hui,YANG You-lin.Comparative study of approximation performance of numerical optimization improved BP neural networks[J].Shandong Science,2014,27(1):68-72. |
| |
| Authors: | DING Shuo CHANG Xiao-heng WU Qing-hui YANG You-lin |
| |
| Institution: | School of Industry, Bohai University, Jinzhou 121013, China |
| |
| 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. |
| |
| Keywords: | numerical optimization BP neural networks approximation performance comparative study |
| 本文献已被 CNKI 维普 等数据库收录！ |
| 点击此处可从《山东科学》浏览原始摘要信息 |
| 点击此处可从《山东科学》下载免费的PDF全文 |
|
