کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10324189 | 661413 | 2005 | 33 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
An approach for on-line extraction of fuzzy rules using a self-organising fuzzy neural network
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
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چکیده انگلیسی
This paper presents a hybrid neural network, called the self-organising fuzzy neural network (SOFNN), to extract fuzzy rules from the training data. The first hidden layer of this network consists of ellipsoidal basis function (EBF) neurons. Every EBF neuron in the SOFNN has both a centre vector and a width vector. Neurons are organised by the network itself. The methods of the structure and parameter learning, based on new adding and pruning techniques and a recursive learning algorithm, are simple and effective, with a high accuracy and a compact structure. Simulations show that the SOFNN has the capability to encode fuzzy rules in the resulting network.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Fuzzy Sets and Systems - Volume 150, Issue 2, 1 March 2005, Pages 211-243
Journal: Fuzzy Sets and Systems - Volume 150, Issue 2, 1 March 2005, Pages 211-243
نویسندگان
Gang Leng, Thomas Martin McGinnity, Girijesh Prasad,