[1]严丽,王启志.GA-Elman网络的网络控制系统预测[J].华侨大学学报(自然科学版),2014,35(6):620-624.[doi:10.11830/ISSN.1000-5013.2014.06.0620]
　YAN Li,WANG Qi-zhi.Network Control System Prediction Based on GA-Elman Network[J].Journal of Huaqiao University(Natural Science),2014,35(6):620-624.[doi:10.11830/ISSN.1000-5013.2014.06.0620]
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GA-Elman网络的网络控制系统预测()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第35卷
期数:
2014年第6期
页码:
620-624
栏目:
出版日期:
2014-11-20

文章信息/Info

Title:
Network Control System Prediction Based on GA-Elman Network
文章编号:
1000-5013(2014)06-0620-05
作者:
严丽;  王启志
华侨大学 机电及自动化学院, 福建 厦门 361021
Author(s):
YAN Li;  WANG Qi-zhi
College of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021, China
关键词:
网络控制系统;  时延采样值;  Elman神经网络;  遗传算法
Keywords:
network control system;  delay sampling value;  Elman neural network;  genetic algorithm
分类号:
TP183;TP273
DOI:
10.11830/ISSN.1000-5013.2014.06.0620
文献标志码:
A
摘要:
为了消除网络时延对网络控制系统的影响,采用Elman神经网络预测系统时延采样值,并用遗传算法优化神经网络权值阈值.实验仿真表明:经遗传算法优化后的Elman神经网络具有很好的预测精度及动态性能,能够消除时延的影响,并验证了该方法对时延采样值预测的有效性.
Abstract:
In order to eliminate the effects of network delay on the network control system, this paper uses Elman neural network to predict the system delay sampling value and genetic algorithm to optimize the neural network weights threshold. The experimental simulation shows that Elman neural network optimized by genetic algorithm has good prediction accuracy and dynamic performance and can eliminate the influence of time delay. The method that can eliminate the effects of network delay.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2014-04-01
通信作者: 王启志(1971-),男,副研究员,主要从事复杂过程控制和智能控制的研究.E-mail:wangqz@hqu.edu.cn.
基金项目: 福建省自然科学基金资助项目(A0640004); 华侨大学高层次人才科研启动项目(13BS305); 华侨大学横向科研资助项目(43201142)
更新日期/Last Update: 2014-11-20