应用神经网络预测巷道围岩位移

Tang Jun-Yi, Zhang Min, Z. Miao, Y. Wan-jun, Tian Yu
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引用次数: 0

摘要

应用人工智能方法解决地下工程问题。首先,分析了影响矿井巷道围岩位移的因素,并将影响巷道位移的4个指标作为神经网络的输入层;然后,以巷道接近率作为网络的输出层,构建巷道围岩位移的神经网络预测模型;最后,学习和训练模型。预测结果表明,该方法具有一定的实用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Applying Neural Network to Predict Roadway Surrounding Rock Displacement
Apply artificial intelligence methods to solve underground engineering problems. First, the factors affecting the displacement of the surrounding rock of the mine roadway are analyzed, and the four indexes that affect the displacement of the roadway are used as the input layer of the neural network. Then, the approach rate of the roadway is used as the output layer of the network to construct the neural network prediction model of the roadway surrounding rock displacement. Finally, learn and train the model. The prediction result shows that it has a certain practical value.
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