Title of article :
Solving Fuzzy Equations Using Neural Nets with a New Learning Algorithm
Author/Authors :
جعفريان، احمد نويسنده Jafarian, Ahmad , معصومي نيا، صفا نويسنده Department of Mathematics, Urmia Branch, Islamic Azad University, Urmia, Iran Measoomy nia, Safa , جعفري، راحله نويسنده Department of Mathematics, science and research Branch, Islamic Azad University, Arak, Iran jafari, Raheleh
Issue Information :
فصلنامه با شماره پیاپی 10 سال 2012
Pages :
13
From page :
33
To page :
45
Abstract :
Artificial neural networks have the advantages such as learning, adaptation, fault-tolerance, parallelism and generalization. This paper mainly intends to offer a novel method for finding a solution of a fuzzy equation that supposedly has a real solution. For this scope, we applied an architecture of fuzzy neural networks such that the corresponding connection weights are real numbers. The suggested neural net can adjust the weights using a learning algorithm that based on the gradient descent method. The proposed method is illustrated by several examples with computer simulations.
Journal title :
Journal of Advances in Computer Research
Serial Year :
2012
Journal title :
Journal of Advances in Computer Research
Record number :
709764
Link To Document :
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