A Neural Computational Intelligence Method Based on Legendre Polynomials for Fuzzy Fractional Order Differential Equation-Reference-Cited by-同舟云学术

A Neural Computational Intelligence Method Based on Legendre Polynomials for Fuzzy Fractional Order Differential Equation

Published:2016-12-01 Issue:2 Volume:12 Page:67-82
ISSN:1336-9180
Container-title:Journal of Applied Mathematics, Statistics and Informatics
language:en
Short-container-title:

Author:

Khan N. A.¹,Shaikh A.²,Zahoor Raja M. A.³,Khan S.²

Affiliation:

1. Department of Mathematics, University of Karachi, Karachi 75270, Pakistan

2. Department of Mathematics, of Karachi, Karachi 75270, Pakistan

3. Department of Electrical Engineering, COMSATS Institute of Information Technology, Attock, Pakistan

Abstract

Abstract In this article, Legendre simulated annealing, neural network (LSANN) is designed for fuzzy fractional order differential equations, which is employed on fractional fuzzy initial value problem (FFIVP) with triangular condition. Here, Legendre polynomials are used to modify the structure of neural networks with a Taylor series approximation of the tangent hyperbolic as activation function while the network adaptive coefficients are trained in the procedure of simulated annealing to optimize the residual error. The computational results are depicted in terms of numerical values to compare them with previous results.

Publisher

Walter de Gruyter GmbH

Subject

General Medicine

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