Energy consumption forecasting in process industry using support vector machines and particle swarm optimization
作者： Milan R. Rapaić , Milena R. Petković , Boris B. Jakovljević
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摘要: In this paper, Support Vector Machines (SVMs) are applied in predicting energy consumption the first phase of oil refining at a particular refinery. During cross-validation process SVM training Particle Swarm Optimization (PSO) algorithm was utilized selection free parameters, widths radial basis functions to be exact. Incorporation PSO into has greatly enhanced quality prediction.
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