Machine learning approach to solve Bessel’s equation

Loganathan, S. and Sarala, S. and Balasubramanian, A. and Madhavi, M. Radha (2021) Machine learning approach to solve Bessel’s equation. In: UNSPECIFIED.

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Abstract

In this paper, the machine learning technique is studied to solve Friedrich Wilhelm Bessel's differential equation. The Wolfram Mathematica and MATLAB software are considered some of the machine learning tools. The necessary concepts and procedures of the Bessel function, Laplace Transformation, Frobenius method, and Power series method are discussed and compared with machine learning vast software. The Solution of Friedrich Wilhelm Bessel's differential equation has been depicted graphically and described. In the future, the emerging applications of the significant areas, equations can be examined with R, Scilab, and python software with various initial and boundary conditions for finding solutions. © 2021 Elsevier B.V., All rights reserved.

Item Type: Conference or Workshop Item (Paper)
Subjects: Mathematics > Computational Mathematics
Divisions: Arts and Science > School of Arts and Science, Chennai > Mathematics
Depositing User: Unnamed user with email techsupport@mosys.org
Last Modified: 03 Dec 2025 11:55
URI: https://vmuir.mosys.org/id/eprint/3099

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