2020
DOI: 10.3390/fractalfract4020021
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Exact Solution of Two-Dimensional Fractional Partial Differential Equations

Abstract: In this study, we examine adapting and using the Sumudu decomposition method (SDM) as a way to find approximate solutions to two-dimensional fractional partial differential equations and propose a numerical algorithm for solving fractional Riccati equation. This method is a combination of the Sumudu transform method and decomposition method. The fractional derivative is described in the Caputo sense. The results obtained show that the approach is easy to implement and accurate when applied to various fractiona… Show more

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Cited by 30 publications
(10 citation statements)
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“…The advantage of the double Sumudu transform is it gives a rapid convergence of the exact solution without any restrictive assumption of the solution compared to other known methods (see [27]). Unfortunately, this transform fails to solve nonlinear partial differential equations like other integral transforms; to solve this problem, this transform is often combined with other methods like the variational method [28], reduced differential transform method [29], double integral transform (Laplace-Sumudu transform) method [30], Adomian decomposition method [25,31], and homotopy perturbation method [20,32].…”
Section: Introductionmentioning
confidence: 99%
“…The advantage of the double Sumudu transform is it gives a rapid convergence of the exact solution without any restrictive assumption of the solution compared to other known methods (see [27]). Unfortunately, this transform fails to solve nonlinear partial differential equations like other integral transforms; to solve this problem, this transform is often combined with other methods like the variational method [28], reduced differential transform method [29], double integral transform (Laplace-Sumudu transform) method [30], Adomian decomposition method [25,31], and homotopy perturbation method [20,32].…”
Section: Introductionmentioning
confidence: 99%
“…In general, higher performance of the fractional calculus is demonstrated by reduced error levels created during an estimating procedure. Various approximation and methodologies, like the fractional Adomian decomposition method (FADM) [8][9][10], fractional homotopy method (FHPM) [11,12,13], fractional function decomposition method [14,15], fractional variational iteration method (FVIM) [16][17][18], fractional reduce differential transform method (FRDTM) [18,19,20,21], fractional differential transform method [22,23,24], fractional Laplace variational iteration method [25][26][27][28][29][30][31][32], fractional Laplace homotopy perturbation method (FLHPM) [33], fractional Laplace decomposition method (FLDM) [34,35], fractional Sumudu homotopy analysis method [36], fractional Sumudu variational iteration method (FVIM) [37,38], fractional Sumudu decomposition method (FSDM) [39][40][41], fractional natural decomposition method (FNDM) [42,43], fractional Sumudu homotopy perturbation method (FSHPM) [44,45], energy balance method (EBM) [46], power series methods (PSM) [47], have been used in latest years to analyze partial di...…”
Section: Introductionmentioning
confidence: 99%
“…In recent decades, many of the numerical and analytical techniques have been implemented to solve fractional-order PDEs, such as the fractional variational iteration method [23,34,42,44,45], fractional differential transform method [25,36,46], fractional series expansion method [9,29], fractional Sumudu variational iteration method [20,31], fractional natural decomposition method [32,38], fractional Sumudu decomposition method [17,30,33], fractional Sumudu homotopy perturbation method [28], fractional reduce differential transform method [24,26,41], fractional Adomian decomposition method [16,21,47], fractional Laplace decomposition method [27], fractional Laplace homotopy perturbation method [14], fractional Laplace variational iteration method [13,15,18,35,37], variational iteration method [4][5][6][7][8] and local mesh less УДК 517.95 2020 Mathematics Subject Classification: 34K37, 45J99, 34A08.…”
Section: Introductionmentioning
confidence: 99%