|本期目录/Table of Contents|

[1]刘 俊.思维进化算法在BP神经网络拟合非线性函数中的应用研究[J].绵阳师范学院学报,2015,(02):79-83.
 LIU Jun.On Application of Mind Evolutionary Algorithm in BP Neural Network Fitting Nonlinear Function[J].Journal of Mianyang Normal University,2015,(02):79-83.
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思维进化算法在BP神经网络拟合非线性函数中的应用研究(PDF)
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《绵阳师范学院学报》[ISSN:1672-612X/CN:51-1670/G]

卷:
期数:
2015年02期
页码:
79-83
栏目:
计算机与网络技术
出版日期:
2015-02-15

文章信息/Info

Title:
On Application of Mind Evolutionary Algorithm in BP Neural Network Fitting Nonlinear Function
文章编号:
1672-612x(2015)02-0079-05
作者:
刘 俊
商洛学院电子信息与电气工程学院, 陕西商洛 726000
Author(s):
LIU Jun
School of Electronic Information and Electrical Engineering, Shangluo University, Shangluo, Shaanxi 726000
关键词:
思维进化算法 BP神经网络 函数拟合
Keywords:
mind evolutionary algorithm BP neural network function fitting
分类号:
TP183
DOI:
-
文献标志码:
A
摘要:
直接使用BP神经网络拟合非线性函数,具有预测精度差、收敛速度慢等缺点.该文提出利用极强全局搜索能力的思维进化算法来优化BP神经网络.首先根据BP神经网络拓扑结构构建思维进化算法模型,然后用思维进化算法得到的最优解作为BP神经网络的初始权值和阈值,最后利用MATLAB软件对多个非线性函数进行拟合仿真实验,比较思维进化算法优化BP神经网络和单纯使用BP神经网络的预测结果.数据表明,优化后的BP神经网络具有更高的拟合精度和更短的网络训练时间.
Abstract:
Owing to the poor accuracy, slow convergence speed and other shortcomings after the direct application of BP neural network in the fitting of nonlinear functions, this paper proposed that BP neural network can be optimized by mind evolutionary algorithm, which enjoys strong global search ability. Firstly, the mind evolutionary algorithm model is constructed based on neural network topology; then, it is used to get the optimal solutions, which is served as initial weights and the threshold value of BP neural network; lastly, the MATLAB software is used to simulate multiple nonlinear function fitting, comparing the different results between optimized BP neural network and simply application of the BP neural network. Statistics indicate that the optimized BP neural network enjoys higher accuracy and shorter training time.

参考文献/References:

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备注/Memo

备注/Memo:
作者简介:刘俊(1986- ),男,山西大同人,硕士,助教,研究方向:计算机测控系统.
更新日期/Last Update: 2015-02-15