人工神经网络氡气灾害模型在铀矿山的应用  

The Application of Artificial Neural Network in Radon Disaster Model of Uranium Mining

作　　者：朱煜峰[1,2] 朱国根 周世健[1] 

机构地区：[1]东华理工大学,江西抚州344000 [2]中南大学,湖南长沙410083 [3]中核抚州金安铀业有限公司,江西抚州344300

出　　处：《铀矿地质》2012年第1期47-51,共5页Uranium Geology

基　　金：国家自然科学基金(编号:40874010);核资源与环境教育部重点实验室资助项目(编号:101115)

摘　　要：对多层前馈神经网络模型(BP神经网络)的结构特点、数据分析、学习方法和过程等内容做了分析。以中核抚州金安铀业有限公司铀矿山氡气状态为学习训练样本及预测样本,建立铀矿山氡气灾害模型。讨论了基于BP神经网络技术的氡气灾害模型分析方法及其有效性。通过实例样本的训练检验表明,采用人工神经网络方法对铀矿山氡灾害预测取得了比较满意的效果,为神经网络在铀矿山氡气灾害预报的应用提供了可行性。The structural features,data analysis and learning process of feed-forward neural network（BP ANN） were analyzed at first.Rodon sample from Fuzhou Jinan Uranium Industry Limited Company were used to training the network and make the forecast then,and a forecasting model was established for the radon disaster in uranium mines.The method and effectiveness of BP neural network in predicting radon disaster was discussed.The test of training samples shew that the BP network had gotten fairly satisfied result in predicting mine radon disaster.

关 键 词：多层前馈神经网络 氡气 学习样本 灾害模型 

分 类 号：P619.14[天文地球—矿床学] TP183[天文地球—地质学]