Roof displacement prediction algorithm of goaf in Gongchangling Open-pit Mine

Aiming at the prediction of goaf roof displacement in Gongchangling Open-pit Mine,based on the basic principle of K-means clustering algorithm,the hierarchical iterative clustering algorithm is proposed,and the Puata criterion is combined to automatically eliminate the clutter data and random error data in real-time acquisition data. Then the gray prediction model is used to predict displacement-time series. The predicted results are in good agreement with the measured data,which verifies the reliability and correctness of the proposed algorithm. According to the prediction results,it can be justified that the displacement variation of goaf roof in Gongchangling Open-pit Mine is stable and there is no risk of instability in the short term.