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Estimation of froth flotation recovery and collision probability based on operational parameters using an artificial neural network 被引量:5

Estimation of froth flotation recovery and collision probability based on operational parameters using an artificial neural network
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摘要 An artificial neural network and regression procedures were used to predict the recovery and collision probability of quartz flotation concentrate in different operational conditions. Flotation parameters, such as dimensionless numbers (Froude, Reynolds, and Weber), particle size, air flow rate, bubble diameter, and bubble rise velocity, were used as inputs to both methods. The linear regression method shows that the relationships between flotation parameters and the recovery and collision probability of flotation can achieve correlation coefficients (R2) of 0.54 and 0.87, respectively. A feed-forward artificial neural network with 3-3-3-2 arrangement is able to simultaneously estimate the recovery and collision probability as the outputs. In testing stages, the quite satisfactory correlation coefficient of 0.98 was achieved for both outputs. It shows that the proposed neural network models can be used to determine the most advantageous operational conditions for the expected recovery and collision probability in the froth flotation process. An artificial neural network and regression procedures were used to predict the recovery and collision probability of quartz flotation concentrate in different operational conditions. Flotation parameters, such as dimensionless numbers (Froude, Reynolds, and Weber), particle size, air flow rate, bubble diameter, and bubble rise velocity, were used as inputs to both methods. The linear regression method shows that the relationships between flotation parameters and the recovery and collision probability of flotation can achieve correlation coefficients (R2) of 0.54 and 0.87, respectively. A feed-forward artificial neural network with 3-3-3-2 arrangement is able to simultaneously estimate the recovery and collision probability as the outputs. In testing stages, the quite satisfactory correlation coefficient of 0.98 was achieved for both outputs. It shows that the proposed neural network models can be used to determine the most advantageous operational conditions for the expected recovery and collision probability in the froth flotation process.
出处 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2010年第5期526-534,共9页 矿物冶金与材料学报(英文版)
关键词 FLOTATION RECOVERY COLLISION PROBABILITY neural networks flotation recovery collision probability neural networks
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