基于人工神经网络的矿井构造定量评价  

Quantitative Evaluation of Mining Structure on The Basis of Artificial Nerve 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,西安710054

出　　处：《中国煤田地质》2001年第3期73-74,共2页Coal Geology of China

基　　金：煤炭科学基金资助项目97地10406部分成果

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,利用东坡井田已知资料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。It has probed into artificial nerve n etwork methods of mining structural quantitative evaluation,and discu ssed the problems of construct and optimization and so forth,on import layer and h idden layer and export layer of BP mod el,combine with Dongpo mine field and used informati ons of Dongpo mine field with optimis tical separate method and insert value method of order geological quantity to obtain learn ing sample book,and evaluation on unknown units,get through training of learning sample book.

关 键 词：人工神经网络 矿井构造 定量评价 煤矿 

分 类 号：TD163.1[矿业工程—矿山地质测量]