utilizing a new feed-back fuzzy neural network for solving a system of fuzzy equations

نویسندگان

a. jafarian

department of mathematics, urmia branch, islamic azad university, urmia, iran. s. measoomy nia

department of mathematics, urmia branch, islamic azad university, urmia, iran.

چکیده

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.

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عنوان ژورنال:
international journal of industrial mathematics

جلد ۵، شماره ۴، صفحات ۲۹۹-۳۰۷

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