A stable numerical algorithm based on support vector regression for fractional initial value problems

Li, X. Y.

doi:10.1016/j.aml.2026.110028

A stable numerical algorithm based on support vector regression for fractional initial value problems

2026-09-29

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DOI：10.1016/j.aml.2026.110028

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Solutions to fractional-order initial value problems are typically non-smooth, which poses challenges for numerical methods. Although the Mittag-Leffler function is well suited to capturing such non-smooth behavior, collocation methods based on it often lead to ill-conditioned systems, resulting in numerical instability. In this letter, we propose a new method for solving fractional-order initial value problems by combining the Mittag-Leffler reproducing kernel function (RKF) with support vector regression.

Keywords:

Support vector regression

Fractional initial value problems

Mittag-Leffler kernel function

A stable numerical algorithm based on support vector regression for fractional initial value problems

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