2004, Volume 6, Issue 4
Strategic Study of CAE >> 2004, Volume 6, Issue 4
A Method of Constructing Fuzzy Neural Network Based on Rough Set Theory
Electronic Information and Control Engineering College , Beijing University of Technology , Beijing 100022 , China
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Abstract
A new method of constructing fuzzy neural network is presented and Rough set theory is applied to this method. Since Rough set theory has strong numeric analyzing ability and fuzzy neural network has exact function approaching ability, their combination can produce a neural network model with good intelligibility and fast convergence. First, some rules are acquired from given data set by rough set theory. Then, these rules are applied to constructing neural cell numbers and relative parameters in fuzzy neural network. Finally the initial network is trained by BP arithmetic and the whole network design is finished. Also in this paper, an example of nonlinear function approaching is discussed and the feasibility of this method is proved.
Keywords
fuzzy neural network ; rough set ; acquire rule ; function approaching
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References
[ 1 ] Zadeh L A. Fuzzy logic, neural networks and soft computing[J].Communications of the ACM,1994, 37(3):77~84
[ 2 ] 李士勇.模糊控制神经控制和智能控制论［M］.哈尔滨：哈尔滨工业大学出版社，1996
[ 3 ] Yasdi R. Combining rough sets learning and neural learning method to deal with uncertain and imprecise information[J].Neuro-Computing,1995,7(1):61 ~84
[ 4 ] 王士同.神经模糊系统及其应用［M］.北京：北京航空航天大学出版社，1998.179～186
[ 5 ] 王国胤.Rough集理论与知识获取［M］.西安：西安交通大学出版社，2001
[ 6 ] 易继错.智能控制技术［M］.北京：北京工业大学出版社，1999
[ 7 ] Rudin W.Principles of Mathematical Analysis[M]. New York McGRAW-HILL Book Company,1976. 159~165
[ 8 ] 李永敏.根据粗糙集理论进行BP网络设计的研究［J］．系统工程理论与实践，1999,19（4）：62～69
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