Article ID Journal Published Year Pages File Type
496220 Applied Soft Computing 2013 11 Pages PDF
Abstract

Graphical abstractFigure optionsDownload full-size imageDownload as PowerPoint slideHighlights•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.

Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
Authors
,