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

作　　者：朱宝龙[1] 夏玉成[1] 

机构地区：[1]西安科技学院地质系,陕西西安710054

出　　处：《煤田地质与勘探》2001年第6期15-17,共3页Coal Geology & Exploration

基　　金：原煤炭科学基金项目 ( 97地 10 4 0 6)

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 。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.

关 键 词：人工神经网络 矿井构造 定量评价 煤矿 

分 类 号：P618.11[天文地球—矿床学] TD163.1[天文地球—地质学]