Accurate computational study between spectral and wavelet methods for fractional differential equations

  • Hassan Zedan orcid

    Department of Mathematics, Faculty of Science, Kafrelsheikh University, Kafr El Sheikh 33516, Egypt

  • Nada Okasha orcid

    Department of Mathematics, Faculty of Science, Kafrelsheikh University, Kafr El Sheikh 33516, Egypt

Article ID: 4562
Keywords: fractional differential equations; Caputo fractional derivative; Shifted Chebyshev Tau Method; Shifted Chebyshev Collocation Method; Haar Wavelet Collocation Method; operational matrices; low-regularity benchmark; convergence analysis

Abstract

This paper compares three numerical schemes for Caputo fractional differential equations: the Shifted Chebyshev Tau Method (SCTM), the Shifted Chebyshev Collocation Method (SCCM), and the Haar Wavelet Collocation Method (HWCM). In the two Chebyshev schemes, the unknown solution is approximated by shifted Chebyshev polynomials, whereas the Haar formulation uses localized piecewise-constant basis functions and fractional integration matrices. Each method reduces the governing equation to a finite algebraic system. The original contribution is a controlled like-for-like comparison in which the three formulations use the same numbers of unknowns, common independent test grids, and the same accuracy, conditioning, sparsity, and timing diagnostics. Six benchmark problems with known exact solutions are examined using the balanced approximation sizes N = 4, 8, 16, 32. The first five examples have smooth polynomial solutions. SCTM and SCCM recover the exact profiles to the adopted working precision whenever the exact polynomial lies in the selected approximation space. The sixth example has the nonpolynomial solution u(x) = x 5/2, whose third derivative is unbounded at the left endpoint, and therefore provides a genuine low-regularity convergence test. At N = 32, the maximum errors of SCTM and SCCM are 4.39523 × 106 and 4.31475 × 106 , respectively, whereas HWCM gives 4.33493 × 102 . The results show that the Chebyshev methods provide the highest accuracy for the problems studied, SCCM generally achieves this accuracy with a lower assembly cost than SCTM, and HWCM produces better-conditioned and less dense systems with generally first-order-type convergence.

Published
2026-09-07
How to Cite
Zedan, H., & Okasha, N. (2026). Accurate computational study between spectral and wavelet methods for fractional differential equations. Advances in Differential Equations and Control Processes, 33(3). https://doi.org/10.59400/adecp4562

References

[1]Podlubny I. Fractional Differential Equations: An Introduction to Fractional Derivatives, Fractional Differential

[2]Equations, to Methods of Their Solution and Some of Their Applications. Academic Press; 1999.

[3]Kilbas AA, Srivastava HM, Trujillo JJ. Theory and Applications of Fractional Differential Equations. Elsevier; 2006.

[4]Diethelm K, Ford J. Numerical Solution of the Bagley-Torvik Equation. BIT Numerical Mathematics. 2002; 42(3):

[5]–507. doi: 10.1023/A:1021973025166

[6]El-Mesiry AEM, El-Sayed AMA, El-Saka HAA. Numerical methods for multi-term fractional (arbitrary) orders differential equations. Applied Mathematics and Computation. 2005; 160(3): 683–699. doi:

[7]1016/j.amc.2003.11.026

[8]Zayernouri M, Karniadakis GE. Exponentially accurate spectral and spectral element methods for fractional ODEs.

[9]Journal of Computational Physics. 2014; 257: 460–480. doi: 10.1016/j.jcp.2013.09.039

[10]Arikoglu A, Ozkol I. Solution of fractional differential equations by using differential transform method. Chaos,

[11]Solitons & Fractals. 2007; 34(5): 1473–1481. doi: 10.1016/j.chaos.2006.09.004

[12]Atabakzadeh MH, Akrami MH, Erjaee GH. Chebyshev operational matrix method for solving multi-order

[13]fractional ordinary differential equations. Applied Mathematical Modelling. 2013; 37(20–21): 8903–8911. doi:

[14]1016/j.apm.2013.04.019

[15]Ali KK, El Salam MAA, Mohamed EM. Chebyshev operational matrix for solving fractional order delay-differential

[16]equations using spectral collocation method. Arab Journal of Basic and Applied Sciences. 2019; 26(1): 342–353. doi:

[17]1080/25765299.2019.1629543

[18]Baleanu D, Shiri B, Srivastava HM, et al. A Chebyshev spectral method based on operational matrix for fractional

[19]differential equations involving non-singular Mittag-Leffler kernel. Advances in Difference Equations. 2018; 2018(1):

[20]doi: 10.1186/s13662-018-1822-5

[21]Abdelkawy MA, Amin AZM, Lopes AM, et al. Shifted Fractional-Order Jacobi Collocation Method for Solving

[22]Variable-Order Fractional Integro-Differential Equation with Weakly Singular Kernel. Fractal and Fractional. 2021;

[23](1): 19. doi: 10.3390/fractalfract6010019

[24]Sadiq S, Rehman MU. ψ-shifted operational matrix scheme for fractional partial differential equations. Journal of

[25]Applied Analysis & Computation. 2022; 12(2): 497–516. doi: 10.11948/20210101

[26]Farhood AK, Mohammed OH. Shifted Chebyshev operational matrices to solve the fractional time-delay diffusion

[27]equation. Partial Differential Equations in Applied Mathematics. 2023; 8: 100538. doi: 10.1016/j.padiff.2023.100538

[28]Ahmed HM. Enhanced shifted Jacobi operational matrices of integrals: spectral algorithm for solving some

[29]types of ordinary and fractional differential equations. Boundary Value Problems. 2024; 2024(1): 75. doi:

[30]1186/s13661-024-01880-0

[31]Ahmed HM. Highly Accurate Numerical Method for Solving Fractional Differential Equations with Purely Integral

[32]Conditions. Fractal and Fractional. 2025; 9(7): 407. doi: 10.3390/fractalfract9070407

[33]Ahmed HM, Izadi M, Cattani C. A Spectral Approach to Variable-Order Fractional Differential Equations: Improved

[34]Operational Matrices for Fractional Jacobi Functions. Mathematics. 2025; 13(16): 2544. doi: 10.3390/math13162544

[35]Mason JC, Handscomb DC. Chebyshev Polynomials. Chapman and Hall/CRC; 2002. doi: 10.1201/9781420036114

[36]Canuto C, Hussaini MY, Quarteroni A, et al. Spectral Methods: Fundamentals in Single Domains. Springer Berlin

[37]Heidelberg; 2006. doi: 10.1007/978-3-540-30726-6

[38]Oloniiju SD, Mukwevho N, Tijani YO, et al. Chebyshev Pseudospectral Method for Fractional Differential Equations

[39]in Non-Overlapping Partitioned Domains. AppliedMath. 2024; 4(3): 950–974. doi: 10.3390/appliedmath4030051

[40]El-Sayed AA, Agarwal P. Spectral treatment for the fractional-order wave equation using shifted Chebyshev

[41]orthogonal polynomials. Journal of Computational and Applied Mathematics. 2023; 424: 114933. doi:

[42]1016/j.cam.2022.114933

[43]Babaei A, Banihashemi S, Moghaddam BP, et al. Hexic-Chebyshev Collocation Method for Solving Distributed-Order

[44]Time-Space Fractional Diffusion Equations. Axioms. 2025; 14(7): 515. doi: 10.3390/axioms14070515

[45]Abdelgaber KM, Fathy M, Hassan A, et al. Computational study of fractional partial differential equations using the

[46]second-kind Chebyshev collocation technique with error analysis. Boundary Value Problems. 2026; 2026(1): 20. doi:

[47]1186/s13661-025-02202-8

[48]Abd-Elhameed WM, Abdelkawy MA, Alsafri NMA, et al. Numerical Treatment of the Time-Fractional

[49]Kuramoto–Sivashinsky Equation Using a Combined Chebyshev-Collocation Approach. Fractal and Fractional. 2025;

[50](11): 727. doi: 10.3390/fractalfract9110727

[51]Daubechies I. Ten Lectures on Wavelets. Society for Industrial and Applied Mathematics; 1992. doi:

[52]1137/1.9781611970104

[53]Lepik Ü. Numerical solution of differential equations using Haar wavelets. Mathematics and Computers in Simulation.

[54]; 68(2): 127–143. doi: 10.1016/j.matcom.2004.10.005

[55]Li Y, Zhao W. Haar wavelet operational matrix of fractional order integration and its applications in solving

[56]the fractional order differential equations. Applied Mathematics and Computation. 2010; 216(8): 2276–2285. doi:

[57]1016/j.amc.2010.03.063

[58]Shiralashetti SC, Deshi AB. An efficient Haar wavelet collocation method for the numerical solution of multi-term fractional differential equations. Nonlinear Dynamics. 2016; 83(1–2): 293–303. doi: 10.1007/s11071-015-2326-4

[59]Abdeljawad T, Amin R, Shah K, et al. Efficient sustainable algorithm for numerical solutions of systems of fractional

[60]order differential equations by Haar wavelet collocation method. Alexandria Engineering Journal. 2020; 59(4):

[61]–2400. doi: 10.1016/j.aej.2020.02.035

[62]Amin R, Alshahrani B, Mahmoud M, et al. Haar wavelet method for solution of distributed order time-fractional

[63]differential equations. Alexandria Engineering Journal. 2021; 60(3): 3295–3303. doi: 10.1016/j.aej.2021.01.039

[64]Saha Ray S. On Haar wavelet operational matrix of general order and its application for the numerical solution

[65]of fractional Bagley Torvik equation. Applied Mathematics and Computation. 2012; 218(9): 5239–5248. doi:

[66]1016/j.amc.2011.11.007

[67]Mechee MS, Al-Shaher OI, Al-Juaifri GA. Haar wavelet technique for solving fractional differential equations with

[68]an application. AIP Conference Proceedings. 2019; 2086: 030025. doi: 10.1063/1.5095110

[69]Shah K, Khan ZA, Ali A, et al. Haar wavelet collocation approach for the solution of fractional order COVID-19 model

[70]using Caputo derivative. Alexandria Engineering Journal. 2020; 59(5): 3221–3231. doi: 10.1016/j.aej.2020.08.028

[71]Bulut F, Oruc O, Esen A. A 3-Scale Haar Wavelet Collocation Method for Numerical Solution of the Nonlinear Gardner

[72]Equation. Mediterranean Journal of Mathematics. 2025; 22(2): 38. doi: 10.1007/s00009-025-02808-3

[73]Amin R, Shah K, Ahmad H, et al. Haar wavelet method for solution of variable order linear fractional

[74]integro-differential equations. AIMS Mathematics. 2022; 7(4): 5431–5443. doi: 10.3934/math.2022301

[75]Amin R, Ullah R, Khan I, et al. Haar wavelet method with Caputo derivative for solution of a system of

[76]fractional integro-differential equations. Journal of Applied Analysis & Computation. 2025; 15(3): 1641–1658. doi:

[77]11948/20240325

[78]Hamood MM, Sharif AA, Ghadle KP. A unified Haar wavelet collocation framework for fractional Volterra

[79]integro-differential equations with application to tumor-immune dynamics modeling. Scientific Reports. 2026; 16(1):

[80]doi: 10.1038/s41598-026-42803-6

[81]Yi M, Huang J. Wavelet operational matrix method for solving fractional differential equations with variable

[82]coefficients. Applied Mathematics and Computation. 2014; 230: 383–394. doi: 10.1016/j.amc.2013.06.102

[83]Gupta S, Ranta S. Legendre wavelet based numerical approach for solving a fractional eigenvalue problem. Chaos,

[84]Solitons & Fractals. 2022; 155: 111647. doi: 10.1016/j.chaos.2021.111647

[85]Suganthi J, Maury SC. A wavelet-based collocation approach for solving chlorine transport model. Boundary Value

[86]Problems. 2026; 2026(1): 108. doi: 10.1186/s13661-026-02273-1

[87]Chen Y, Yi M, Yu C. Error analysis for numerical solution of fractional differential equation by Haar wavelets method.

[88]Journal of Computational Science. 2012; 3(5): 367–373. doi: 10.1016/j.jocs.2012.04.008

[89]Majak J, Shvartsman B, Pohlak M, et al. Solution of fractional order differential equation by the Haar Wavelet

[90]method. Numerical convergence analysis for most commonly used approach. AIP Conference Proceedings. 2016;

[91]: 480110. doi: 10.1063/1.4952346