Prediction of operational parameters effect on coal flotation using artificial neural network

查看全文 作　　者：E. [1]Jorjani;Sh. [1]Mesroghli;S. Chehreh [1]Chelgani

机构地区：[1]Department of Mining Engineering,Science and Research Branch,Islamic Azad University

出　　处：《Journal of University of Science and Technology Beijing》索引2008年第15卷第5期,共6页

摘　　要：Artificial neural network procedures were used to predict the combustible value (i.e. 100-Ash) and combustible recovery of coal flotation concentrate in different operational conditions. The pulp density,pH,rotation rate,coal particle size,dosage of col-lector,frother and conditioner were used as inputs to the network. Feed-forward artificial neural networks with 5-30-2-1 and 7-10-3-1 arrangements were capable to estimate the combustible value and combustible recovery of coal flotation concentrate respectively as the outputs. Quite satisfactory correlations of 1 and 0.91 in training and testing stages for combustible value and of 1 and 0.95 in training and testing stages for combustible recovery prediction were achieved. The proposed neural network models can be used to determine the most advantageous operational conditions for the expected concentrate assay and recovery in the coal flotation process. 关键词：煤矿浮选选矿方式人工神经网络操作方法

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Prediction of operational parameters effect on coal flotation using artificial neural network

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