A Prediction Model Based on Neural Network and Fuzzy Markov Chain

被引：3

作者：

Liu, Jia ^{[1
]}

Li, Shunxiang ^{[2
]}

Jia, Shusheng ^{[1
]}

机构：

[1] Jilin Univ, Minist Educ, Key Lab Automobile Mat, Changchun 130022, Peoples R China

[2] Guangdong Univ Technol, Coll Automat, Guangzhou, Guangdong 510006, Peoples R China

来源：

2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23 | 2008年

关键词：

BP neural network; Markov chain; Prediction; Nanocomposite materials;

D O I：

10.1109/WCICA.2008.4593023

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In order to solve the problem of random and fluctuation of experiment errors and predication errors of neural network, a neural network model modified by a fuzzy Markov chain was introduced, When neural network was used to predict, the prediction errors between actual value and output value of the network were distributed randomly. That can be simulated by a Markov chain. According to the forecasting property of Markov chain, the prediction errors of neural network can be modified by the fuzzy Markov chain. The addition of fuzzy Markov chain to ANN method can prominently improve the prediction quality. This model was applied to analysis the properties of nano-composite materials. And the result showed it was effective and better than neural network model.

引用

页码：790 / +

页数：2

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