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Hydrogeology Journal

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23-02-2021 | Paper

Risk evaluation of mine-water inrush based on principal component logistic regression analysis and an improved analytic hierarchy process

Authors: Qiang Li, Wanghua Sui

Published in: Hydrogeology Journal | Issue 3/2021

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Abstract

A method of evaluating the risk of floor water inrush using principal component logistic regression analysis (PCLRA) and an improved analytic hierarchy process (IAHP) is presented. The approach was validated by a case study at the Yangcheng coal mine in Shandong Province, China. First, the risk assessment index of floor water inrush was determined based on geological and hydrogeological conditions of the study area. Then, a comprehensive evaluation model (CEM), combining PCLRA with IAHP, was constructed to determine the comprehensive weight of each water-inrush evaluation index. Finally, water-inrush risk zoning was determined with GIS. The results show that the CEM, compared with the water-inrush coefficient method (WICM) traditionally and commonly used in China, has higher fitting accuracy and more detailed division of water-inrush risk areas. This method not only follows the observations in reality, but also fully considers the relative importance of water-inrush evaluation indices. The results can provide a theoretical basis for the safe mining of coal seams above confined groundwater.

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Title: Risk evaluation of mine-water inrush based on principal component logistic regression analysis and an improved analytic hierarchy process
Authors: Qiang Li
Wanghua Sui
Publication date: 23-02-2021
Publisher: Springer Berlin Heidelberg
Published in: Hydrogeology Journal / Issue 3/2021
Print ISSN: 1431-2174
Electronic ISSN: 1435-0157
DOI: https://doi.org/10.1007/s10040-021-02305-3

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