Concentrate Grade Prediction of Gold Ore Based on GA-BP Neural Network

Two prediction models for concentrate grade of gold mine were established respectively by using BP neural network and GA-BP neural network method on the basis of investigation in actual production. 978 groups of data were gathered from actual production, from which the 770 groups was selected for establishing the models, among which 120 groups was used for verification. By analyzing the predictive errors of two models, it is approved that the prediction model based on GA-BP neural network can provide better accuracy: when the relative prediction errors are within + 2% , the prediction accuracy reaches 97.5%.