Journal
APPLIED SOFT COMPUTING
Volume 13, Issue 8, Pages 3597-3607Publisher
ELSEVIER
DOI: 10.1016/j.asoc.2013.04.013
Keywords
Partially fuzzy neural network; System of fuzzy differential equations; Learning algorithm
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Fuzzy neural network (FNN) can be trained with crisp and fuzzy data. This paper presents a novel approach to solve system of fuzzy differential equations (SFDEs) with fuzzy initial values by applying the universal approximation method (UAM) through an artificial intelligence utility in a simple way. The model finds the approximated solution of SFDEs inside of its domain for the close enough neighborhood of the fuzzy initial points. We propose a learning algorithm from the cost function for adjusting of fuzzy weights. At the same time, some examples in engineering and economics are designed. (C) 2013 Elsevier B. V. All rights reserved.
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