Discrimination Method for Water Inrush Source of Mine Based on Rough Sets Theory and BP Neural Network

摘要：

　　Based on rough set theory and BP neural network theory,discriminating method for water inrush source of mine was studied.The chemical indicators of inrush water were chosen to constitute a water sample matrix.First,the rough sets theory was applied to sample information reduction,then the BP neural network was applied to water source discrimination.Discriminating model for water source was established based on rough set theory and BP neural network,and compared with the traditional BP neural network model.Taked Panyi mine in Huainan for example,the results are compared with those of BP neural network model and show that the discriminating method based on rough set theory and BP neural network theory had a higher discrimination accuracy (92.5%)than the BP neural network method(82.5%).The principle of the method was clear and applied easily.

关键词： rough sets BP neural network water inrush source discrimination Panyi mine

作者: YAN Zhen QIAN Jiazhong ZHAO Weidong

作者单位: School of Resources and Environmental Engineering, Hefei University of Technology, Hefei 230009, China

会议类型: 国际会议

会议名称: The 4th International Conference on Environmental Technology and Knowledge Transfer(第四届亚欧环境技术及知识转化国际研讨会(2012ICET))

会议地点: 合肥

会议语种:英文

页码: 821-825

在线出版日期: 2012-05-24（万方平台首次上网日期，不代表论文的发表时间）