Title of article
Prediction of jet penetration depth based on least square support vector machine
Author/Authors
Wang، نويسنده , , Chun-hua and Zhong، نويسنده , , Zhao-ping and Li، نويسنده , , Rui and E، نويسنده , , Jia-qiang، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2010
Pages
8
From page
404
To page
411
Abstract
Experiments to investigate the jet penetration depth were carried out. The jet penetration depth increases with the increase of spouting gas velocity, spouting nozzle diameter and carrier gas density, but decreases with the rise of the static bed height, particle density, particle diameter and fluidized gas rate. The intelligent model to predict the jet penetration depth has been established based on least square support vector machine and adaptive mutative scale chaos optimization algorithm. The prediction performance of the intelligent model is better than empirical correlations and neural network.
Keywords
Spout-fluidized bed , Jet penetration depth , Chaos optimization algorithm , Least square support vector machine
Journal title
Powder Technology
Serial Year
2010
Journal title
Powder Technology
Record number
1699808
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