Prediction of the Recovery Rate of a Gold Mine Based on Double Hidden Layer BP Neural Network
In order to grasp the action law of process factors affecting the actual recovery rate of a gold ore and predict the gold recovery rate,the flotation test was carried out by the method of orthogonal experiment.The sen-sitivity of process factors was analyzed by Pearson coefficient,and the gold recovery rate was predicted by us-ing double hidden layer BP neural network.The results show that the sensitivity of the gold recovery rate to dif-ferent factors in the production process is in descending order:2#oil dosage,sodium sulfide dosage,butyl xan-thate dosage,copper sulfate dosage and grinding fineness.The reasons for the significant differences in the ef-fects of 2#oil dosage,sodium sulfide dosage and butyl xanthate dosage on gold recovery rate were also eluci-dated.On this basis,used three main influencing factors such as 2#oil dosage,the study selected different input layer to the first implicit layer functions,such as tansig,purelin and logsig,and the rest of the activation func-tions remained unchanged.The first hidden layer to the second hidden layer function was logsig,and the second hidden layer to the output layer function was purelin.When research used logsig as the activation function,the fitted degree and accuracy are high,the goodness of fit R2 is 0.9792,and the relative average error is only 0.666%.The model can be used to predict the recovery rate of gold.The research has certain reference signifi-cance for the prediction of metal recovery rate in the production of precious metal mines.
BP neural networkPearson coefficientactivation functioninfluencing factorsgold minerecovery rate
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