DocumentCode :
2477293
Title :
A prediction model based on neural network and fuzzy Markov chain
Author :
Liu, Jia ; Li, Shunxiang ; Jia, Shusheng
Author_Institution :
Key Lab. of Automobile Mater., Jilin Univ., Changchun
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
790
Lastpage :
793
Abstract :
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.
Keywords :
Markov processes; forecasting theory; neural nets; prediction theory; forecasting property; fuzzy Markov chain; neural network; prediction errors; prediction model; Artificial neural networks; Automation; Error correction; Fluctuations; Fuzzy control; Fuzzy neural networks; Intelligent control; Nanostructured materials; Neural networks; Predictive models; BP neural network; Markov chain; Nano-composite materials; Prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
Type :
conf
DOI :
10.1109/WCICA.2008.4593023
Filename :
4593023
Link To Document :
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