The Research of the Flotation Recovery Prediction Methods Based on Advanced LS-SVM
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 .
Y. Zhang et al., "The Research of the Flotation Recovery Prediction Methods Based on Advanced LS-SVM", Applied Mechanics and Materials, Vols. 130-134, pp. 1854-1857, 2012