An Efficient Fractional‐Order Shifted Legendre Function for Solving Multiterm High‐order Fractional‐Differential Equations of Caputo‐Type With Convergence Analysis

ABSTRACT This study introduces a novel numerical technique employing fractional‐order shifted Legendre functions (FSLFs) defined on the interval to address multiterm linear fractional‐differential equations (LFDEs) of high fractional‐integer order of the Caputo type, subject to mixed boundary conditions. The methodology leverages FSLFs in conjunction with the Gauss‐Lobatto point technique. The core objective of this approach is to transform the LFDEs and their associated mixed boundary conditions into a system of matrix equations. The proposed procedure's effectiveness and reliability are thoroughly evaluated via absolute error and error reduction analyses, juxtaposing the computed solutions with exact solutions and established findings from the literature. Furthermore, a residual error correction strategy is integrated to significantly improve the accuracy of the numerical results. The convergence analysis for the proposed method demonstrates that as the number of basis functions increases, the approximate solution monotonically approaches the exact solution. The behavior of the solutions is visually examined through comprehensive graphical representations. All computational tasks and graphical visualizations were executed using Python.

Authors

Institutions

Publication Details

Journal
Mathematical Methods in the Applied Sciences
Published
2025-12-23
DOI
https://doi.org/10.1002/mma.70408
Primary Topic
Fractional Differential Equations Solutions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Efficient Fractional‐Order Shifted Legendre Function for Solving Multiterm High‐order Fractional‐Differential Equations of Caputo‐Type With Convergence Analysis

Rahel Qadir, Shabaz J. Mohammedfaeq
Mathematical Methods in the Applied Sciences
Fractional Differential Equations Solutions
article

An Efficient Fractional‐Order Shifted Legendre Function for Solving Multiterm High‐order Fractional‐Differential Equations of Caputo‐Type With Convergence Analysis

Rahel Qadir, Shabaz J. Mohammedfaeq
article en

Abstract

ABSTRACT This study introduces a novel numerical technique employing fractional‐order shifted Legendre functions (FSLFs) defined on the interval to address multiterm linear fractional‐differential equations (LFDEs) of high fractional‐integer order of the Caputo type, subject to mixed boundary conditions. The methodology leverages FSLFs in conjunction with the Gauss‐Lobatto point technique. The core objective of this approach is to transform the LFDEs and their associated mixed boundary conditions into a system of matrix equations. The proposed procedure's effectiveness and reliability are thoroughly evaluated via absolute error and error reduction analyses, juxtaposing the computed solutions with exact solutions and established findings from the literature. Furthermore, a residual error correction strategy is integrated to significantly improve the accuracy of the numerical results. The convergence analysis for the proposed method demonstrates that as the number of basis functions increases, the approximate solution monotonically approaches the exact solution. The behavior of the solutions is visually examined through comprehensive graphical representations. All computational tasks and graphical visualizations were executed using Python.

Mathematical Methods in the Applied Sciences
University of Sulaimani (IQ)
Openalex Percentile: Top 34%
Fractional Differential Equations Solutions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.