神經網絡在大尺度采空區損傷演化統計與預測中應用

Application of Neural Network to the Statistics and Prediction of Dynamical Damage and Evolutement in the Large Scale Mine-out Area Supported by Rock-Based Composite Materials

摘要: 利用神經網絡結構計算方法對巖石基復合材料支護大尺度采空區動力損傷演化趨勢進行統計和預測,并與工程現場多種方法的綜合監測數據進行了比較,其結果完全吻合.

Abstract: The neural network structural computation method was applied to the trend statistics and prediction of stress evolvement in the large scale mine-out area supported by rock-based composite materials. The predicting values were compared with the in-situ monitoring ones. The results show they are very agreeable.