Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4640730 | Journal of Computational and Applied Mathematics | 2010 | 10 Pages |
Abstract
In this paper, a novel hybrid method based on fuzzy neural network for approximate fuzzy coefficients (parameters) of fuzzy linear and nonlinear regression models with fuzzy output and crisp inputs, 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 parameters, a simple algorithm from the cost function of the fuzzy neural network is proposed. Finally, we illustrate our approach by some numerical examples.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
M. Mosleh, M. Otadi, S. Abbasbandy,