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Learning solutions to two dimensional electromagnetic equations using LS-SVM
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DOI：10.1016/j.neucom.2018.05.035.png)
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Abstract
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In this paper, a new approach based on least squares support vector machines (LS-SVM) is proposed for solving the electromagnetic equations. Firstly, the cubic spline function is employed to smooth the discontinuous boundary. LS-SVM is used to solve the modified problem. Secondly, nonlinear electromagnetic equation is solved by LS-SVM. Finally, multimedia electromagnetic equation is solved by LS-SVM. Same as to the artificial neural networks (ANN), the approximate solutions are composed of two parts. The first part is a known function that satisfies the boundary conditions. The second part is the product of two terms. One term is also a known function which vanished on the boundary. The left part is the combination of kernel functions containing regression parameters. The parameters can be obtained by solving a system of equations. The numerical results show that the proposed method in this paper is feasible. (C) 2018 Elsevier B.V. All rights reserved.
Keywords:
Linear electromagnetic equation
Nonlinear electromagnetic equation
Multimedia electromagnetic equation
Discontinuous boundary conditions
Least squares support vector machines
Cubic spline
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