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