کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
409368 | 679068 | 2007 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Training T-S norm neural networks to refine weights for fuzzy if-then rules
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
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چکیده انگلیسی
This correspondence proposes an approach to learning weights of weighted fuzzy if-then rules. According to a given T-S norm-based reasoning mechanism, this approach first maps a set of weighted fuzzy if-then rules into a feed-forward T-S norm network in which connection weights are just the weights of weighted fuzzy if-then rules, and then trains the T-S norm neural network by a derived gradient descent algorithm. Numerical experiments show that the proposed approach is feasible and quite effective. The main contribution of this correspondence is that the mapping relationship between a set of weighted fuzzy if-then rules and a T-S norm neural network is discovered so that the difficult problem of weight acquisition in weighted fuzzy if-then rules can be converted into the training of a T-S norm neural network. A comparison between our T-S norm neural network system and a similar model (NEFCLASS) is made.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 70, Issues 13â15, August 2007, Pages 2581-2587
Journal: Neurocomputing - Volume 70, Issues 13â15, August 2007, Pages 2581-2587
نویسندگان
Xi-Zhao Wang, Chun-Ru Dong, Tie-Gang Fan,