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- W2099318878 abstract "Support Vector Machines (SVMs) are applied in predicting fuel consumption in the first phase of oil refining at oil refinery “NIS Rafinerija Nafte Novi Sad” in Novi Sad, Serbia. During cross-validation process of the SVM training Particle Swarm Optimization (PSO) algorithm was utilized in selection of free SVM parameters. In particular widths of radial basis functions, as well as widths of regression tube and penalty factor were optimized by means of PSO. Incorporation of PSO into SVM training process has greatly enhanced the quality of prediction." @default.
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- W2099318878 date "2008-09-01" @default.
- W2099318878 modified "2023-09-28" @default.
- W2099318878 title "Electric energy forecasting in crude oil processing using Support Vector Machines and Particle Swarm Optimization" @default.
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- W2099318878 doi "https://doi.org/10.1109/neurel.2008.4685568" @default.
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