FDTD Time Series Extrapolation by the Least Squares Support Vector Machine Method with the Particle Swarm Optimization Technique

Y Yang,Z.B Ye,R.S Chen,Z Liu

doi:10.1109/apmc.2005.1606760

FDTD Time Series Extrapolation by the Least Squares Support Vector Machine Method with the Particle Swarm Optimization Technique

Y Yang, Z.B Ye + Show 2 more

https://doi.org/10.1109/apmc.2005.1606760

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Publication Date: Dec 4, 2005

Citations: 7

Affiliation: Nanjing University of Science and Technology

#Particle Swarm Optimization Technique #Least-squares Support Vector Machines Algorithm + Show 8 more

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Abstract

A new combination of particle swarm optimization (PSO) and least-squares support vector machines (LS-SVM) technique for FDTD time series forecasting is presented. In this paper, the PSO is extended to optimize the hyperparameter used in the LS-SVM algorithm. Numerical simulations demonstrate that the PSO method can efficiently get the optimal value of the hyperparameter used in the LS-SVM algorithm. And the PSO/spl I.bar/LS-SVM method can improve the computational efficiency of the FDTD algorithm when compared with the direct FDTD method.

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