标题:Application of ideal point method in rockburst prediction based on weight back analysis method
作者:Qiu, Daohong ;Zhang, Lewen ;Li, Shucai ;Zhang, Deyong
通讯作者:Qiu, D
作者机构:[Qiu, Daohong ] Geotechnical and Structural Engineering Research Center, Shandong University, China;[Li, Shucai ;Zhang, Deyong ] School of Civil Engin 更多
会议名称:2011 GeoHunan International Conference - Advances in Pile Foundations, Geosynthetics, Geoinvestigations, and Foundation Failure Analysis and Repairs
会议日期:9 June 2011 through 11 June 2011
来源:Geotechnical Special Publication
出版年:2011
期:220 GSP
页码:268-275
DOI:10.1061/47631(410)31
关键词:Predictions; Rocks; Weight
摘要:Rockburst is one of the main geological hazards in high terrestrial stress zone. The prediction of possibility and intensity of rockburst are important issues. Ideal point method is a general multi-objective decision analysis method. The basic process is to construct the ideal solution and anti-ideal solution of evaluation objects, and make the degree of close to the ideal solution or away from the anti-ideal solution as classification criterion. It has not yet seen the application in rockburst prediction. It has great influence to the finial evaluation results for the reasonable weight values of the evaluation indices. Although there are a lot of methods to determine weights recently, these methods have their deficiencies. To solve these problems, weights back analysis method based on optimization theory are used, which changes the directly given weights methods to the problem of back analyzing index weights according to engineering samples. The method is fully derived by engineering samples, and no experience is necessary. Finally, the result using this method shows that this method is reliable. Ideal point method provides a new idea to predict rockburst, and weights back analysis method is universal and can be used in any weights problems. © 2011 ASCE.
收录类别:EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052799032&doi=10.1061%2f47631%28410%2931&partnerID=40&md5=a5862d78847be92d9039b6179521c3df
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