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Title: A new method based on least-squares support vector regression for solving optimal control problems (English)
Author: Bolhassani, Mitra
Author: Dana Mazraeh, Hassan
Author: Parand, Kourosh
Language: English
Journal: Kybernetika
ISSN: 0023-5954 (print)
ISSN: 1805-949X (online)
Volume: 60
Issue: 4
Year: 2024
Pages: 513-534
Summary lang: English
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Category: math
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Summary: In this paper, a new application of the Least Squares Support Vector Regression (LS-SVR) with Legendre basis functions as mapping functions to a higher dimensional future space is considered for solving optimal control problems. At the final stage of LS-SVR, an optimization problem is formulated and solved using Maple optimization packages. The accuracy of the method are illustrated through numerical examples, including nonlinear optimal control problems. The results demonstrate that the proposed method is capable of solving optimal control problems with high accuracy. (English)
Keyword: Least squares support vector machines
Keyword: Optimal control problems
Keyword: Legendre orthogonal polynomials
Keyword: Regression
Keyword: Artificial intelligence
MSC: 49Mxx
MSC: 68T20
DOI: 10.14736/kyb-2024-4-0513
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Date available: 2024-10-17T08:47:56Z
Last updated: 2024-10-17
Stable URL: http://hdl.handle.net/10338.dmlcz/152617
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