Abstract
In this paper, a new hybrid method based on fuzzy neural network (FNN) for approximate solution of fuzzy linear systems of the form \(Ax=d,\) where \(A\) is a square matrix of fuzzy coefficients, \(x\) and \(d\) are fuzzy number vectors, is presented. Here a neural network is considered as a part of a large field called neural computing or soft computing. Moreover, in order to find the approximate solution of an \(n\times n\) system of fuzzy linear equations that supposedly has a unique fuzzy solution, a simple algorithm from the cost function of the FNN is proposed. Finally, we illustrate our approach by some numerical examples.
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We would like to offer particular thanks to Dr M. A. Rezvani for the editing of this paper. We would also like to thank the referees for valuable suggestions.
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Otadi, M., Mosleh, M. & Abbasbandy, S. Numerical solution of fully fuzzy linear systems by fuzzy neural network. Soft Comput 15, 1513–1522 (2011). https://doi.org/10.1007/s00500-010-0685-9
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DOI: https://doi.org/10.1007/s00500-010-0685-9