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IFS-LSSVM and its application in time-delay series prediction
Author(s): 
Pages: 104-110
Year: Issue:  11
Journal: Electric Machines and Control

Keyword:  least squares support machinesfree searchtime-delay seriespredictiontime series;
Abstract: It is difficult to determine the optimal parameters of least squares support vector machine pre-diction model, so a prediction method based on improved free search algorithm ( IFS-LSSVM) was pro-posed to determine the optimal parameters of least squares support vector machines. First, the standard free search algorithm was improved so that it can be applied to the parameter optimization of least squares support vector machines, the improved harmony search algorithm has better optimization performance. Then the least squares support vector machines was applied to predict the time-delay series of the network based on improved free search optimization algorithm. Finally, time-delay series was used as prediction simulation object, genetic algorithm optimized least squares support vector machines ( GA-LSSVM) , par-ticle swarm optimization algorithm optimized least squares support vector machines ( PSO-LSSVM ) , standard grid search method of least squares support vector machines ( Grid-LSSVM) toolbox were com-pared. Simulation comparison results show that the proposed method has higher prediction accuracy and smaller prediction error.
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