An experimental modeling of cyclone separator efficiency with PCA-PSO-SVR algorithm

Accurate prediction of the complicated nonlinear relationship among the grade efficiency, geometrical dimensions, and operating parameters based on limited experimental data is the most effective way to design a high-efficiency cyclone separator. Herein, a hybrid PCA-PSO-SVR model is proposed to pre...

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Veröffentlicht in:	Powder technology Jg. 347; S. 114 - 124
Hauptverfasser:	Zhang, Wei, Zhang, Linlin, Yang, Jingxuan, Hao, Xiaogang, Guan, Guoqing, Gao, Zhihua
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Lausanne Elsevier B.V 01.04.2019 Elsevier BV
Schlagworte:	Algorithms Correlation coefficient Correlation coefficients Cyclone separator Cyclone separators Efficiency Experimental data Grade efficiency Kernel functions Mathematical models Model accuracy Model testing Parameters Particle swarm optimization powders prediction Predictions Pretreatment Principal component analysis Principal components analysis Random sampling Regression analysis sampling Separators Statistical sampling Support vector machines Support vector regression algorithm Test sets Grade efficiency Cyclone separator Particle swarm optimization Support vector regression algorithm Principal component analysis
ISSN:	0032-5910, 1873-328X
Online-Zugang:	Volltext
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