Numerical Simulation of Fuzzy Nonlinear Equations by Feedforward Neural Networks
نویسندگان
چکیده
Fuzzy set theory is considered as a suitable setting in order to take vagueness of real world problems into considerations. Operating with fuzzy dependencies among fuzzy data is a challenging problem, because it requires special arithmetic and a powerful optimization technique. The concept of fuzzy numbers and arithmetic operation with these numbers were first introduced and investigated by Zadeh [1]. One of the major applications of fuzzy number arithmetic is nonlinear equations whose parameters are all or partially represented by fuzzy numbers [2-5] Standard analytical techniques like Buckley and Qu method [6-9] can not be suitable for equations such as
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