A HEURISTIC COMPUTING APPROACH USING SEQUENTIAL QUADRATIC PROGRAMMING TO SOLVE THE FIFTH KIND OF INDUCTION MOTOR MODEL

Zulqurnain Sabir (), Muhammad Asif Zahoor Raja, S. R. Mahmoud (), Juan L. G. Guirao and Juan M. Sã Nchez ()
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Zulqurnain Sabir: Department of Mathematics and Statistics, Hazara University, Mansehra, Pakistan
Muhammad Asif Zahoor Raja: ��Future Technology Research Center, National Yunlin University of Science and Technology 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, R. O. C.
S. R. Mahmoud: ��GRC Department, Faculty of Applied Studies, King Abdulaziz University, Jeddah, Saudi Arabia
Juan L. G. Guirao: �Department of Applied Mathematics and Statistics, Technical University of Cartagena Hospital de Marina, 30203 Cartagena, Spain¶Nonlinear Analysis and Applied Mathematics (NAAM)-Research Group, Department of Mathematics, Faculty of Science, King Abdulaziz University, P. O. Box 80203, Jeddah 21589, Saudi Arabia∥Laboratory of Theoretical Cosmology, International Centre of Gravity and Cosmos, TUSUR, 634050 Tomsk, Russia
Juan M. Sã Nchez: �Department of Applied Mathematics and Statistics, Technical University of Cartagena Hospital de Marina, 30203 Cartagena, Spain

FRACTALS (fractals), 2022, vol. 30, issue 10, 1-13

Abstract: The purpose of the current investigation is to solve the fifth kind of induction motor model using an advanced computational scheme by operating the artificial neural networks (ANNs), global scheme as genetic algorithm (GA) along with the rapid local search sequential quadratic programming technique (SQPT), i.e. ANN-GA-SQPT. ANNs are implemented to discretize the fifth kind of induction motor model to express the merit function based on the mean square error. The numerical presentation of the proposed ANN-GA-SQPT is pragmatic for three different problems based on the fifth kind of induction motor model to authenticate the efficacy, consistency and importance of the proposed ANN-GA-SQPT. Moreover, statistical representations are provided in order to check the precision, convergence and accuracy of the present ANN-GA-SQPT.

Keywords: Induction Motor Nonlinear Models; Statistical Performances; Artificial Neural Networks; Sequential Quadratic Programming Technique; Genetic Algorithm (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0218348X2240240X

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