UniFIDES: Universal Fractional Integro-Differential Equation Solvers

• URL: http://arxiv.org/abs/2407.01848v2
• Date: Mon, 8 Jul 2024 13:18:17 GMT
• Title: UniFIDES: Universal Fractional Integro-Differential Equation Solvers
• Authors: Milad Saadat, Deepak Mangal, Safa Jamali,
• Abstract summary: This work introduces the Universal Fractional Integro-Differential Equation Solvers (UniFIDES) UniFIDES is a comprehensive machine learning platform designed to expeditiously solve a variety of FIDEs in both forward and inverse directions. Our results highlight UniFIDES' ability to accurately solve a wide spectrum of integro-differential equations and offer the prospect of using machine learning platforms universally.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The development of data-driven approaches for solving differential equations has been followed by a plethora of applications in science and engineering across a multitude of disciplines and remains a central focus of active scientific inquiry. However, a large body of natural phenomena incorporates memory effects that are best described via fractional integro-differential equations (FIDEs), in which the integral or differential operators accept non-integer orders. Addressing the challenges posed by nonlinear FIDEs is a recognized difficulty, necessitating the application of generic methods with immediate practical relevance. This work introduces the Universal Fractional Integro-Differential Equation Solvers (UniFIDES), a comprehensive machine learning platform designed to expeditiously solve a variety of FIDEs in both forward and inverse directions, without the need for ad hoc manipulation of the equations. The effectiveness of UniFIDES is demonstrated through a collection of integer-order and fractional problems in science and engineering. Our results highlight UniFIDES' ability to accurately solve a wide spectrum of integro-differential equations and offer the prospect of using machine learning platforms universally for discovering and describing dynamical and complex systems.

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