来兴平, 张立杰, 蔡美峰. 神经网络在大尺度采空区损伤演化统计与预测中应用[J]. 工程科学学报, 2003, 25(4): 300-303. DOI: 10.13374/j.issn1001-053x.2003.04.003
引用本文: 来兴平, 张立杰, 蔡美峰. 神经网络在大尺度采空区损伤演化统计与预测中应用[J]. 工程科学学报, 2003, 25(4): 300-303. DOI: 10.13374/j.issn1001-053x.2003.04.003
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LAI Xingping, ZHANG Lijie, CAI Meifeng. 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[J]. Chinese Journal of Engineering, 2003, 25(4): 300-303. DOI: 10.13374/j.issn1001-053x.2003.04.003
Citation: LAI Xingping, ZHANG Lijie, CAI Meifeng. 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[J]. Chinese Journal of Engineering, 2003, 25(4): 300-303. DOI: 10.13374/j.issn1001-053x.2003.04.003
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神经网络在大尺度采空区损伤演化统计与预测中应用

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
  • 摘要: 利用神经网络结构计算方法对岩石基复合材料支护大尺度采空区动力损伤演化趋势进行统计和预测,并与工程现场多种方法的综合监测数据进行了比较,其结果完全吻合.

     

    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.

     

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