标题:A Research on the Methods for Prediction of the Slope Stability of Open-pit Mine
作者:Feng, Xiwen; Guo, Yue; Li, Junyong
通讯作者:Feng, XW;Feng, XW;Feng, XW
作者机构:[Feng, Xiwen] Shandong Univ Sci & Technol, State Key Lab Min Disaster Prevent & Control Shan, Qingdao, Peoples R China.; [Feng, Xiwen] Shandong Univ 更多
会议名称:9th China-Russia Symposium on Coal in the 21st Century - Mining, Intelligent Equipment and Environment Protection
会议日期:OCT 18-21, 2018
来源:PROCEEDINGS OF THE 9TH CHINA-RUSSIA SYMPOSIUM COAL IN THE 21ST CENTURY: MINING, INTELLIGENT EQUIPMENT AND ENVIRONMENT PROTECTION
出版年:2018
卷:176
页码:73-77
关键词:slope stability; back propagation; naive bayes classifier; support; vector machine; decision tree; prediction
摘要:In order to improve the slope stability of open-pit mine, this paper proposed four prediction methods BP (Back Propagation) Neural Network, Naive Bayes Classifier, Decision Tree and Support Vector Machine for predicting the classification of slope stability of open-pit mine. Firstly, the sample data of slope stability in open-pit mine are preprocessed, and the new sample data are obtained after data standardization, discretization and attribute reduction. Then, the corresponding prediction model is established by selecting different methods. All the four methods have been successfully applied to the prediction of 8 groups of samples to be tested. In order to determine the optimal method, the detailed accuracy and node error rate are compared to analyze the prediction results. The research shows that the BP neural network has high reliability and good practicability in the evaluation of the slope stability of open-pit mine.
收录类别:CPCI-S
资源类型:会议论文
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