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There is a significant number of research projects using differential equations to model important and complex problems of engineering and other scientific knowledge areas. This paper investigates the potential that computational algorithms have to determine analytical solutions for ordinary and partial differential equations. In order to do so, the evolutionary method of genetic programming and the automatic differentiation method are applied. Using the MatLab programming environment, several GPAD algorithms are developed and problems of distinct differential equations are addressed. The results are promising, with exact solutions obtained for most of the addressed equations, including ones that commercial systems could not find a symbolic solution to. The conclusion is that GPAD algorithms can be used to discover analytic solutions for ordinary differential equations and partial differential equations.
Ana Carolina Abreu. 2026. \u201cApplications of Genetic Programming and Automatic Differentiation Algorithms in the Solution of Ordinary and Partial Differential Equations\u201d. Global Journal of Research in Engineering - J: General Engineering GJRE-J Volume 22 (GJRE Volume 22 Issue J2): .
Crossref Journal DOI 10.17406/gjre
Print ISSN 0975-5861
e-ISSN 2249-4596
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Total Score: 104
Country: Brazil
Subject: Global Journal of Research in Engineering - J: General Engineering
Authors: Ana Carolina Abreu, Marco Aurélio Pacheco, Valdir Lobão, Douglas Dias (PhD/Dr. count: 0)
View Count (all-time): 225
Total Views (Real + Logic): 1499
Total Downloads (simulated): 40
Publish Date: 2026 01, Fri
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There is a significant number of research projects using differential equations to model important and complex problems of engineering and other scientific knowledge areas. This paper investigates the potential that computational algorithms have to determine analytical solutions for ordinary and partial differential equations. In order to do so, the evolutionary method of genetic programming and the automatic differentiation method are applied. Using the MatLab programming environment, several GPAD algorithms are developed and problems of distinct differential equations are addressed. The results are promising, with exact solutions obtained for most of the addressed equations, including ones that commercial systems could not find a symbolic solution to. The conclusion is that GPAD algorithms can be used to discover analytic solutions for ordinary differential equations and partial differential equations.
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