标题:An attribute recognition model to predict the groundwater potential of sandstone aquifers in coal mines
作者:Shi, Shou-Qiao; Wei, Jiu-Chuan; Xie, Dao-Lei; Yin, Hui-Yong; Zhang, Wei-Jie; Li, Li-Yao
作者机构:[Shi, Shou-Qiao; Wei, Jiu-Chuan; Xie, Dao-Lei; Yin, Hui-Yong; Zhang, Wei-Jie; Li, Li-Yao] Shandong Univ Sci & Technol, Coll Earth Sci & Engn, Qingdao 更多
通讯作者:Wei, JC
通讯作者地址:[Wei, JC]Shandong Univ Sci & Technol, Coll Earth Sci & Engn, Qingdao 266590, Peoples R China.
来源:JOURNAL OF EARTH SYSTEM SCIENCE
出版年:2019
卷:128
期:3
DOI:10.1007/s12040-019-1100-2
关键词:Groundwater potential; attribute recognition; confidence criterion;; improved score criterion
摘要:The groundwater potential prediction of sandstone aquifers is an important pre-requisite for the implementation of reasonable and effective measures to prevent mine water inrush disasters. In this study, an attribute recognition model was combined with entropy weighting to predict the groundwater potential of sandstone aquifers in coal mines. Five evaluation indices were selected to predict groundwater potential, such as sandstone thickness, sandstone lithology coefficient, flushing fluid consumption, fracture fractal dimension and fold fractal dimension. On the basis of data analysis, the groundwater potential was classified into four levels. Confidence and improved score criteria were applied to attribute recognition. The main advantages of this model are that it enables both the prediction and quantification of the groundwater potential of sandstone aquifers. The model's results were compared with those from a comprehensive geographic information system evaluation. The final model results were in good agreement with the observed results, proving that this attribute recognition model is accurate and effective for groundwater potential prediction.
收录类别:SCIE
资源类型:期刊论文
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