Applying the Fractional Cubic Spline Method to Solve Dynamic Systems Numerically.

In this work, we present a new numerical technique for solving systems of differential equations in arising dynamical systems that is based on fractional cubic spline interpolation. The spline consists of several dimensions, and one of the fractional dimensions is α = 5 3 . In order to estimate the...

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Publicado en:Journal of Basrah Researches (Sciences) Vol. 52; no. 1; pp. 1 - 14
Autores principales: Mohammed, Karwan S., Hamasalh, Faraidun K.
Formato: Artículo
Publicado: Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) 2026
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Acceso en línea:Ver este registro en EBSCOhost
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        atl: Applying the Fractional Cubic Spline Method to Solve Dynamic Systems Numerically.
      aug:
        au:
          Mohammed, Karwan S.
          Hamasalh, Faraidun K.
        affil:
          University of Sulaimani, Department of Mathematics, College of Education, Sulaimani, Iraq.
          Sulaimani Polytechnic University, Bakrajo Technical Institute, Sulaimani, Iraq.
      su:
        Dynamical systems
        Differential equations
        Error analysis in mathematics
        MatLab (Computer software)
        Nonlinear systems
        Numerical analysis
        Interpolation
      sug:
        subj:
          Dynamical systems
          Differential equations
          Error analysis in mathematics
          MatLab (Computer software)
          Nonlinear systems
          Numerical analysis
          Interpolation
      keyword:
        and convergence analysis
        Caputo fractional derivative
        computational modelling
        Spline approximation
        النمذجة الحسابية
        تحليل الاستقرار
        سبلاين التقريب
        مشتق كابوتو الكسري
      ab: In this work, we present a new numerical technique for solving systems of differential equations in arising dynamical systems that is based on fractional cubic spline interpolation. The spline consists of several dimensions, and one of the fractional dimensions is α = 5 3 . In order to estimate the solution of nonlinear or linear dynamical systems, the suggested method builds a fractional cubic spline with suitable continuity and differentiability constraints and applies it iteratively. We can find the results for each step, and the error rate decreases, which in our sample makes the relative error close to 107 However, this method requires tracking the dynamic system at each step, using the previous step, which takes a lot of time. Therefore, we rely on MATLAB here. Better modeling of systems having memory effects or hereditary properties which are prevalent in many physical, biological, and engineering problems is made possible by the addition of fractional variables. The method's correctness and efficacy are demonstrated by numerical trials, which also show strong agreement with analytical or benchmark solutions.
      pubtype: Academic Journal
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    language: English
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