Department of Mathematics, Urmia Branch, Islamic Azad University, Urmia, Iran.
Abstract
This paper intends to offer a new iterative method based on arti cial neural networks for finding solution of a fuzzy equations system. Our proposed fuzzi ed neural network is a ve-layer feedback neural network that corresponding connection weights to output layer are fuzzy numbers. This architecture of arti cial neural networks, can get a real input vector and calculates its corresponding fuzzy output. In order to nd the approximate solution of the fuzzy system that supposedly has a real solution, rst a cost function is de ned for the level sets of the fuzzy network and target output. Then a learning algorithm based on the gradient descent method is used to adjust the crisp input signals. The present method is illustrated by several examples with computer simulations.
Jafarian, A., & Measoomy Nia, S. (2013). Utilizing a new feed-back fuzzy neural network for solving a system of
fuzzy equations. International Journal of Industrial Mathematics, 5(4), 299-307.
MLA
A. Jafarian; S. Measoomy Nia. "Utilizing a new feed-back fuzzy neural network for solving a system of
fuzzy equations". International Journal of Industrial Mathematics, 5, 4, 2013, 299-307.
HARVARD
Jafarian, A., Measoomy Nia, S. (2013). 'Utilizing a new feed-back fuzzy neural network for solving a system of
fuzzy equations', International Journal of Industrial Mathematics, 5(4), pp. 299-307.
VANCOUVER
Jafarian, A., Measoomy Nia, S. Utilizing a new feed-back fuzzy neural network for solving a system of
fuzzy equations. International Journal of Industrial Mathematics, 2013; 5(4): 299-307.
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