Solving Fuzzy Equations Using Neural Nets with a New Learning Algorithm
سال انتشار: 1391
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 443
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شناسه ملی سند علمی:
JR_JACR-3-4_004
تاریخ نمایه سازی: 16 شهریور 1395
چکیده مقاله:
Artificial neural networks have the advantages such as learning,adaptation, fault-tolerance, parallelism and generalization. This paper mainlyintends to offer a novel method for finding a solution of a fuzzy equation thatsupposedly has a real solution. For this scope, we applied an architecture offuzzy neural networks such that the corresponding connection weights are realnumbers. The suggested neural net can adjust the weights using a learningalgorithm that based on the gradient descent method. The proposed method isillustrated by several examples with computer simulations.
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نویسندگان
Ahmad Jafarian
Department of Mathematics, Urmia Branch, Islamic Azad University, Urmia, Iran
Safa Measoomy Nia
Department of Mathematics, Urmia Branch, Islamic Azad University, Urmia, Iran
Raheleh Jafari
Department of Mathematics, science and research Branch, Islamic Azad University, Arak, Iran