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Artificial Neural Networks for Predicting Rockburst in Deep Mining

机译:人工神经网络在深部采矿中预测岩爆

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Rockburst is a kind of dynamic instability phenomenon for surrounding rock mass in deep mining.It has complicated nonlinear relationship between rockburst and its factors.Based on the analysis of main factors influencing rockburst, the mining depth H, the ratio of rock's maximal tangential stress to rock's uniaxial compressive strength, the ratio of rock's uniaxial compressive strength to rock's uniaxial tensile strength, and the elastic energy index was selected as the prediction indexes of rockburst.The model to predict rockburst was established by applying the theory of artificial neural network (ANN).A large amount of on-site data was used as learning and training samples.Then the predicted results from the model and theoretical results are compared and analyzed.The results show that it is feasible and appropriate to select mining depth H as a main factor, the model is valid to predict rockburst in deep mining by ANN.
机译:岩爆是一种深部开采围岩动力失稳现象,它与岩爆及其影响因素之间存在复杂的非线性关系。在分析影响岩爆的主要因素,开采深度H,最大切向应力与岩心切应力之比的基础上,进行了研究。选择岩石的单轴抗压强度,岩石的单轴抗压强度与岩石的单轴抗拉强度之比以及弹性能指数作为岩爆预测指标。运用人工神经网络理论建立岩爆预测模型。 。大量的现场数据被用作学习和训练样本,然后对模型的预测结果和理论结果进行了比较和分析。结果表明,选择开采深度H为主要因素是可行和适当的。 ,该模型可有效地通过ANN预测深部开采的岩爆。

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