东坡井田矿井构造的人工神经网络定量评价

以东坡井田为例介绍了人工 神经网络方法在矿井构造定量评价中的应用。首先在分析了东坡井田矿井构造主要影响因素基础上，确定了12个指标作为指标；然后详细叙述了神经网络输入层、隐层及输出层神经元个数的确定以及利用有序的质量最优分割方法和插值法得到训练样本；最后经过学习对网络进行训练，利用此网络对划分出的东坡井田的评价单元进行评价取得了良好的效果。

Quantitative Evaluation of Mining Structure of Dengyo Mine Based on the Artificial Neural Network

The paper discuses the application of artificial neural network in quantitative evaluation of mining structure by the example of Dengyo Mine. Firstly on the base of analyzing main factors of mining structure, 12 indexes are decided as evaluating indexes; Secondly, in detail it introduces how to the determine the numbers of input layer, hidden layer and output layer, and how to get the training samples by the methods of optimizing division and inserted value; Finally, after BP network being trained, it tries to evaluate the unknown unites of Dengyo Mine, the result of assessment is feasible.