ELECTRIC LOAD FORECASTING BASED ON SUPPORT VECTOR MACHINE OPTIMIZED
Changing electrical load is a stationary stochastic process depending on many factors. To handle the raw observational data is using support vector machines to reduce the dimension of the training set. To predict power consumption method is chosen support vector machines. Advantage of this method is that the parameters of the regression model are based on quadratic programming problem having a unique solution.Optimizing parameters of kernal functions implemented based on particle swarm optimization algorithm. Research on the simulation confirm the efficiency of the proposed approach.
Authors: N. D. Polyakhov, I. A. Prikhodko, Van Efen
Direction: Automation and Control
Keywords: Optimization, prediction of power consumption, the method of support vector machines, particle swarm optimization algorithm.
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