Numerical Analysis and Iterative Methods for Fractional Differential Equations

A special issue of Fractal and Fractional (ISSN 2504-3110). This special issue belongs to the section "Numerical and Computational Methods".

Deadline for manuscript submissions: 13 June 2026 | Viewed by 2072

Special Issue Editors


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Guest Editor
Faculty of Engineering, Free University of Bozen-Bolzano, 39100 Bolzano, Italy
Interests: numerical analysis; iterative methods; simultaneous methods; fractal; multidimensional dynamics; stability analysis; fractional differential equations; nonlinear fractional equations; fuzzy fractional differential equation

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Guest Editor
Faculty of Engineering, Free University of Bozen-Bolzano, 39100 Bozen-Bolzano, Italy
Interests: numerical analysis; numerical mathematics; partial/fractional differential equations; fractional diffusion equations

Special Issue Information

Dear Colleagues,

Fractional calculus and fractional differential equations have become essential modelling tools in science and engineering for their enhanced ability to model complex systems with greater accuracy. By extending traditional calculus to non-integer orders, these mathematical tools provide a deeper understanding of systems characterized by memory effects, hereditary properties, and anomalous diffusion. Applications of fractional calculus span diverse fields such as control theory, signal processing, materials science, and bioengineering, where they improve the precision of models for viscoelastic materials, electrochemical processes, and biological systems. Due to the difficulty of obtaining exact solutions for fractional differential equations, numerical analysis plays a crucial role.

The aim of this Special Issue is to develop and analyze numerical, semi-numerical, and analytical schemes for approximating fractional differential equations, with applications across various science and engineering disciplines, including biomedical, mechanical, and chemical engineering. This Special Issue will also focus on the dynamical behaviors of numerical methods, offering insights into their convergence behaviors, stability, consistency, and efficiency.

We invite researchers to submit original articles presenting new developments and analyses of numerical techniques for solving fractional differential equations in engineering and applied sciences. Submissions should contribute to the advancement of numerical methods and their application to real-world problems, showcasing the potential of fractional calculus in enhancing model accuracy and understanding complex systems. Potential research topics include, but are not limited to, the following themes:

  • Numerical methods and computational techniques for fractional differential equations;
  • Stability and consistency of single and multi-step methods for fractional differential equations;
  • Local and global convergence of iterative methods for nonlinear fractional equations;
  • Fractional-order iterative-numerical schemes for nonlinear equations;
  • Dynamical behavior of numerical schemes for fractional differential equations;
  • Hybrid fractional-order numerical iterative schemes;
  • Fractional-order numerical schemes based on artificial neural networks;
  • Fractional-order numerical schemes for unconstrained optimizations problems;
  • Iterative methods for fractional differential equations in finance and economics;
  • Fractal behavior of fractional-order numerical schemes for nonlinear equations;
  • Numerical methods for fractional-order epidemic models;
  • Topological methods for fractional-order nonlinear equations;
  • Fractional-order numerical schemes for systems of nonlinear equations;
  • Numerical schemes for fractional nonlinear equations in physics, biology, and engineering;
  • Numerical schemes for fuzzy fractional differential equations;
  • Hybrid block methods for fractional-order differential equations;
  • Applications of fractional differential equations in control systems and signal processing;
  • Comparative analysis of fractional differential equation solvers;
  • Error analysis and adaptive methods for fractional differential equations.

Dr. Mudassir Shams
Dr. Bruno Carpentieri
Guest Editors

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Keywords

  • fractional differential equations
  • fractional-order differential equations
  • nonlinear fractional equations
  • fuzzy fractional differential equations
  • numerical methods and computational techniques
  • stability and consistency
  • local and global convergence
  • iterative methods
  • dynamical behaviors
  • topological methods
  • hybrid block methods
  • comparative analysis
  • error analysis and adaptive methods
  • applications of fractional differential equations in systems and signal processing
  • applications of nonlinear fractional equations in physics, biology, and engineering

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Published Papers (3 papers)

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Research

19 pages, 3038 KB  
Article
Dynamic Analysis of a Family of Iterative Methods with Fifth-Order Convergence
by Xiaofeng Wang and Shaonan Guo
Fractal Fract. 2025, 9(12), 783; https://doi.org/10.3390/fractalfract9120783 - 1 Dec 2025
Viewed by 184
Abstract
In this paper, a new class of fifth-order Chebyshev–Halley-type methods with a single parameter is proposed by using the polynomial interpolation method. The convergence order of the new method is proved. The dynamic behavior of the new method on quadratic polynomials [...] Read more.
In this paper, a new class of fifth-order Chebyshev–Halley-type methods with a single parameter is proposed by using the polynomial interpolation method. The convergence order of the new method is proved. The dynamic behavior of the new method on quadratic polynomials P(x)=(xa)(xb) is analyzed, the strange fixed points and the critical points of the operator are obtained, the corresponding parameter planes and dynamic planes are drawn, the stability and convergence of the iterative method are visualized, and some parameter values with good properties are selected. The fractal results of the new method corresponding to different parameters about polynomial G(x) are plotted. Numerical results show that the new method has less computing and higher computational accuracy than the existing Chebyshev–Halley-type methods. The fractal results show the new method has good stability and convergence. The numerical results of different iteration methods are compared and agree with the results of dynamic analysis. Full article
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23 pages, 545 KB  
Article
Reconstruction of an Unknown Input Function in a Multi-Term Time-Fractional Diffusion Model Governed by the Fractional Laplacian
by Eman Alruwaili, Mustapha Benoudi, Abdeldjalil Chattouh and Hamed Ould Sidi
Fractal Fract. 2025, 9(11), 713; https://doi.org/10.3390/fractalfract9110713 - 5 Nov 2025
Viewed by 437
Abstract
In the present work, we aim to study the inverse problem of recovering an unknown spatial source term in a multi-term time-fractional diffusion equation involving the fractional Laplacian. The forward problem is first analyzed in appropriate fractional Sobolev spaces, establishing the existence, uniqueness, [...] Read more.
In the present work, we aim to study the inverse problem of recovering an unknown spatial source term in a multi-term time-fractional diffusion equation involving the fractional Laplacian. The forward problem is first analyzed in appropriate fractional Sobolev spaces, establishing the existence, uniqueness, and regularity of solutions. Exploiting the spectral representation of the solution and properties of multinomial Mittag–Leffler functions, we prove uniqueness and derive a stability estimate for the spatial source term from finaltime observations. The inverse problem is then formulated as a Tikhonov regularized optimization problem, for which existence, uniqueness, and strong convergence of the regularized minimizer are rigorously established. On the computational side, we propose an efficient reconstruction algorithm based on the conjugate gradient method, with temporal discretization via an L1-type scheme for Caputo derivatives and spatial discretization using a Galerkin approach adapted to the nonlocal fractional Laplacian. Numerical experiments confirm the accuracy and robustness of the proposed method in reconstructing the unknown source term. Full article
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44 pages, 1707 KB  
Article
A High-Order Fractional Parallel Scheme for Efficient Eigenvalue Computation
by Mudassir Shams and Bruno Carpentieri
Fractal Fract. 2025, 9(5), 313; https://doi.org/10.3390/fractalfract9050313 - 13 May 2025
Viewed by 765
Abstract
Eigenvalue problems play a fundamental role in many scientific and engineering disciplines, including structural mechanics, quantum physics, and control theory. In this paper, we propose a fast and stable fractional-order parallel algorithm for solving eigenvalue problems. The method is implemented within a parallel [...] Read more.
Eigenvalue problems play a fundamental role in many scientific and engineering disciplines, including structural mechanics, quantum physics, and control theory. In this paper, we propose a fast and stable fractional-order parallel algorithm for solving eigenvalue problems. The method is implemented within a parallel computing framework, allowing simultaneous computations across multiple processors to improve both efficiency and reliability. A theoretical convergence analysis shows that the scheme achieves a local convergence order of 6κ+4, where κ(0,1] denotes the Caputo fractional order prescribing the memory depth of the derivative term. Comparative evaluations based on memory utilization, residual error, CPU time, and iteration count demonstrate that the proposed parallel scheme outperforms existing methods in our test cases, exhibiting faster convergence and greater efficiency. These results highlight the method’s robustness and scalability for large-scale eigenvalue computations. Full article
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