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FDTD time series extrapolation by the least squares support vector machine method with the particle swarm optimization technique

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4 Author(s)
Yang, Y. ; Dept. of Commun. Eng., Nanjing Univ. of Sci. & Technol., China ; Chen, R.S. ; Ye, Z.B. ; Liu, Z.

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_LS-SVM method can improve the computational efficiency of the FDTD algorithm when compared with the direct FDTD method.

Published in:

Microwave Conference Proceedings, 2005. APMC 2005. Asia-Pacific Conference Proceedings  (Volume:4 )

Date of Conference:

4-7 Dec. 2005