International Journal of Partial Differential Equations and Applications
ISSN (Print): 2376-9548 ISSN (Online): 2376-9556 Website: http://www.sciepub.com/journal/ijpdea Editor-in-chief: Mahammad Nurmammadov
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International Journal of Partial Differential Equations and Applications. 2017, 5(1), 1-9
DOI: 10.12691/ijpdea-5-1-1
Open AccessArticle

Artificial Neural Network for Solving Fuzzy Differential Equations under Generalized H – Derivation

Mazin H. Suhhiem1,

1Department of Statistics, University of Sumer, Alrifaee, Iraq

Pub. Date: April 22, 2017

Cite this paper:
Mazin H. Suhhiem. Artificial Neural Network for Solving Fuzzy Differential Equations under Generalized H – Derivation. International Journal of Partial Differential Equations and Applications. 2017; 5(1):1-9. doi: 10.12691/ijpdea-5-1-1

Abstract

The aim of this work is to present a novel approach based on the artificial neural network for finding the numerical solution of first order fuzzy differential equations under generalized H-derivation. The differentiability concept used in this paper is the generalized differentiability since a fuzzy differential equation under this differentiability can have two solutions. The fuzzy trial solution of fuzzy initial value problem is written as a sum of two parts. The first part satisfies the fuzzy condition, it contains no adjustable parameters. The second part involves feed-forward neural networks containing adjustable parameters. Under some conditions the proposed method provides numerical solutions with high accuracy.

Keywords:
fuzzy differential equation artificial neural network generalized H-derivation error function trial solution

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