کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
496220 | 862852 | 2013 | 11 صفحه PDF | دانلود رایگان |

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• We consider a system of fuzzy differential equations.
• We employ partially fuzzy neural network for solving system of fuzzy differential equations.
• We propose a learning algorithm from the cost function for adjusting of weights.
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.
Journal: Applied Soft Computing - Volume 13, Issue 8, August 2013, Pages 3597–3607