Electromechanical equipment state forecasting based on genetic algorithm – support vector regression

► Electromechanical equipment state forecasting model is established by using genetic algorithm-support vector regression. ► Genetic algorithm is employed to choose the training parameters of support vector regression. ► Leave-one-out cross-validation(LOOCV) is adopted to evaluate the fitness of the...

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Vydané v:	Expert systems with applications Ročník 38; číslo 7; s. 8399 - 8402
Hlavní autori:	Huang, Ji, Bo, Yucheng, Wang, Huiyuan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.07.2011
Predmet:	Electromechanical equipments Expert systems Forecasting Genetic algorithm Genetic algorithms Industrial smokes and gas turbine Mathematical analysis Mathematical models Prediction Regression State vectors Support vector machine Support vector machines Vectors (mathematics) Support vector machine Electromechanical equipments Genetic algorithm Industrial smokes and gas turbine Prediction
ISSN:	0957-4174, 1873-6793
On-line prístup:	Získať plný text
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