Numerical Solution of Fuzzy Differential Equations Under Generalized Differentiability By Fuzzy Neural Network

In this paper, we interpret a fuzzy differential equation by using the strongly generalized differentiability concept. utilizing the generalized characterization theorem. then a novel hybrid methodbased on learning algorithm of fuzzy neural network for the solution of differential equation withfuzzy initial value is presented. here neural network is considered as a part of large field called neuralcomputing or soft computing. the model finds the approximated solution of fuzzy differential equation inside of its domain for the close enough neighborhood of the fuzzy initial point. we propose alearning algorithm from the cost function for adjusting of fuzzy weights.