Wind weather prediction based on multi-output least squares support vector regression optimised by bat algorithm
by Dingcheng Wang; Yiyi Lu; Beijing Chen; Youzhi Zhao
International Journal of Embedded Systems (IJES), Vol. 12, No. 2, 2020

Abstract: As a kind of clean energy, wind energy is widely disseminated and has been widely researched. Compared with other methods, the support vector machine algorithm is more logical. Least squares support vector machine can improve training efficiency. Therefore, the method of multi-output least squares support vector regression is used to forecast the wind speed and wind direction in this paper. The bat algorithm is simple in structure and easy to understand. It has been applied to solve optimisation problems with MSVR. Compared with single output support vector machines, multi-output support vector machine readily solves problems of complex structure. The simulation model is established to predict the value of wind speed and wind direction by using different algorithms. The simulation results show that the multi-output least squares support vector machines prediction model based on bat optimisation algorithm has better feasibility and effectiveness.

Online publication date: Tue, 10-Mar-2020

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