朱宝龙, 夏玉成. 人工神经网络在矿井构造定量评价中的应用[J]. 煤田地质与勘探, 2001, 29(6): 15-17.
引用本文: 朱宝龙, 夏玉成. 人工神经网络在矿井构造定量评价中的应用[J]. 煤田地质与勘探, 2001, 29(6): 15-17.
ZHU Bao-long, XIA Yu-cheng. Quantitative evaluation of mining structure based on the artificial neural network[J]. COAL GEOLOGY & EXPLORATION, 2001, 29(6): 15-17.
Citation: ZHU Bao-long, XIA Yu-cheng. Quantitative evaluation of mining structure based on the artificial neural network[J]. COAL GEOLOGY & EXPLORATION, 2001, 29(6): 15-17.

人工神经网络在矿井构造定量评价中的应用

Quantitative evaluation of mining structure based on the artificial neural network

  • 摘要: 探讨了矿井构造定量评价的人工神经网络方法, 结合东坡井田实际, 重点讨论了 BP模型的输入层、隐含层和输出层的构置和优选等问题, 并使用有序地质量最优分割方法和插值法得到学习样本, 经过学习样本的训练, 对未知单元进行评价取得了良好的效果。

     

    Abstract: How to use BP network to evaluate mine structure is discussed in this paper.A detailed research is focused on the designing and optimum selecting of the input, hidden and output layers in the model in conjunction with the concrete situation of Dongpo Mine.The methods of optimizing division and inserted value are used to get training samples.After BP network being trained, it tries to evaluate the unknowm unites, resulting in feasible assessment result.

     

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