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Prediction of jet penetration depth based on least square support vector machine
Authors:Chun-hua Wang  Zhao-ping Zhong  Jia-qiang E
Affiliation:a School of Energy and Environment, Southeast University, Nanjing, 211189, PR China
b School of Mechanical and Automotive Engineering, Hunan University, Changsha, 410082, PR China
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   Least square support vector machine   Chaos optimization algorithm
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