Computational Mathematics and Computer Modeling with Applications (CMCMA)

A novel Müntz polynomial-based least squares support vector regression method for solving fractional optimal control problems

https://doi.org/10.48308/CMCMA.4.2.9
Volume 4, Issue 2
September 2025
Pages 9-22
Computational Mathematics and Computer Modeling with Applications (CMCMA)

Document Type : Regular paper

Authors

Mitra Bolhassani 1
Kourosh Parand 2

1 Department of Applied Mathematics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran

2 Department of Computer and Data Sciences, Shahid Beheshti University, Tehran, Iran

Abstract
This paper introduces a novel integration of Müntz polynomials into the Least Squares Support Vector Regression framework for addressing fractional optimal control problems. By utilizing Müntz basis functions as the mapping mechanism to project the problem into a higher-dimensional space, the proposed method reformulates the optimization challenge and resolves it efficiently through Maple's optimization tools. The effectiveness of this technique is validated via numerical experiments on benchmark fractional optimal control cases. Outcomes reveal that the approach delivers high precision in solving these problems, surpassing existing techniques in terms of accuracy and efficiency.

Keywords

Least squares support vector machines
Fractional optimal control problems
Müntz polynomials
Regression
Artificial intelligence
  • Receive Date 19 August 2025
  • Revise Date 26 September 2025
  • Accept Date 02 October 2025

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