A Generalized Operational Matrix of Mixed Partial Derivative Terms With Applications To Multi-Order Fractional Partial Differential Equations
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Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Open Access Color
GOLD
Green Open Access
No
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Publicly Funded
No
Abstract
In this paper, a computational approach based on the operational matrices in conjunction with orthogonal shifted Legendre polynomials (OSLPs) is designed to solve numerically the multi-order partial differential equations of fractional order consisting of mixed partial derivative terms. Our computational approach has ability to reduce the fractional problems into a system of Sylvester types matrix equations which can be solved by using MATLAB builtin function lyap (.). The solution is approximated as a basis vectors of OSLPs. The efficiency and the numerical stability is examined by taking various test examples. (C) 2021 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University.
Description
Keywords
Mixed Partial Derivative Terms, Operational Matrices, Legendre Polynomials, Caputo Derivative, Multi-Term And Multi-Order Fractional Partial Differential Equations, Operational matrices, Legendre polynomials, Multi-term and Multi-order Fractional partial differential equations, TA1-2040, Engineering (General). Civil engineering (General), Mixed partial derivative terms, Caputo derivative
Turkish CoHE Thesis Center URL
Fields of Science
0103 physical sciences, 01 natural sciences
Citation
Talib, Imran...et al. (2022). "A generalized operational matrix of mixed partial derivative terms with applications to multi-order fractional partial differential equations", Alexandria Engineering Journal, Vol. 61, No. 1, pp. 135-145.
WoS Q
Q1
Scopus Q
Q1

OpenCitations Citation Count
9
Source
Alexandria Engineering Journal
Volume
61
Issue
1
Start Page
135
End Page
145
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CrossRef : 12
Scopus : 12
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Mendeley Readers : 8
SCOPUS™ Citations
11
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Web of Science™ Citations
11
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Page Views
3
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1.09040702
Sustainable Development Goals
11
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