Paper Title:
The Research of the Flotation Recovery Prediction Methods Based on Advanced LS-SVM
  Abstract

Flotation recovery is an important index of flotation process, in order to change the existing detection methods of low accuracy , a soft measurement model of flotation recoveries is proposed based on improved weighted LS - SVM. According to the flotation foam characteristics and the corresponding relation of flotation recovery, the fuzzy C-means clustering method is used for flotation characteristics of data processing , the image characteristic values as prediction model input and using genetic algorithm to optimize the parameters of the model. The result show that the modified algorithm can overcome a prediction standard model LS - SVM algorithm parameter optimization shortage, and have better forecasting effect which provide effective protection for flotation process operation and flotation operation stable operation optimization .

  Info
Periodical
Edited by
Han Zhao
Pages
1854-1857
DOI
10.4028/www.scientific.net/AMM.130-134.1854
Citation
Y. Zhang, J. Zhu, T. Liu, "The Research of the Flotation Recovery Prediction Methods Based on Advanced LS-SVM", Applied Mechanics and Materials, Vols. 130-134, pp. 1854-1857, 2012
Online since
October 2011
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