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Research and Application of Data Classification in Risk Prediction for Tailings Reservoirs

Aiming to minimize the risk of dam failures during the operation and use of tailings ponds, this paper proposes a method for analyzing and predicting risk by analyzing the data of a tailings reservoir online monitoring system through data classification. The text is supported by the operational risk monitoring and sensing data of a tailings pond. The risk monitoring index system and the monitoring and early warning model are constructed. The data classification and regression analysis methods are used to demonstrate the analysis process of some safety indicators, and the tailings reservoir risk monitoring and early warning system is constructed. Thus, the monitoring, assessment, early warning and trend analysis of the major hazard source risks in tailings ponds are performed. The results show that the method has certain predictive and early warning functions for the safe operation of tailings ponds and provides important reference data for government departments and enterprises, allowing them to monitor and address the safe operation of tailings ponds.