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A Single Layer Functional Link Artificial Neural Network based on Chebyshev Polynomials for Neural Evaluations of Nonlinear Nth Order Fuzzy Differential Equations Cover

A Single Layer Functional Link Artificial Neural Network based on Chebyshev Polynomials for Neural Evaluations of Nonlinear Nth Order Fuzzy Differential Equations

Annals of West University of Timisoara - Mathematics and Computer Science
Volume 56 (2018): Issue 1 (July 2018)
By: Asmat Ara,  Oyoon Abdul Razzaq and  Najeeb Alam Khan  
Open Access
|Dec 2018

Authors

Asmat Ara

noble.asmat@yahoo.com

Department of Computer Science, Muhammad Ali Jinnah University, Karachi, Pakistan

Oyoon Abdul Razzaq

oyoon.abdulrazzaq@yahoo.com

Department of Humanities and Social Sciences, Bahria University, Karachi, Pakistan

Najeeb Alam Khan

njbalam@yahoo.com

Department of Mathematics, University of Karachi, Pakistan
DOI: https://doi.org/10.2478/awutm-2018-0001 | Journal eISSN: 1841-3307 | Journal ISSN: 1841-3293
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Language: English
Page range: 3 - 22
Submitted on: Mar 14, 2016
|
Accepted on: Nov 4, 2017
|
Published on: Dec 7, 2018
Published by: West University of Timisoara
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Keywords:
gH-differentiability,
fuzzy-valued function,
nonlinear fuzzy differential equation,
neural network
Related subjects:
Mathematics,
General mathematics

© 2018 Asmat Ara, Oyoon Abdul Razzaq, Najeeb Alam Khan, published by West University of Timisoara
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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