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Paper
Title

Solving Fuzzy Equations Using Neural Nets with a New Learning Algorithm

Year: 1391
COI: JR_JACR-3-4_004
Language: EnglishView: 287
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Authors

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

Abstract:

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.

Keywords:

Fuzzy equations , Fuzzy feed-forward neural network (FFNN) , Cost function , Learning algorithm

Paper COI Code

This Paper COI Code is JR_JACR-3-4_004. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/488381/

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Jafarian, Ahmad and Measoomy Nia, Safa and Jafari, Raheleh,1391,Solving Fuzzy Equations Using Neural Nets with a New Learning Algorithm,https://civilica.com/doc/488381

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Scientometrics

The specifications of the publisher center of this Paper are as follows:
Type of center: Azad University
Paper count: 3,738
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