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Multisource Information Risk Evaluation Technology of Mine Water Inrush Based on VWM: A Case Study of Weng’an Coal Mine
Author(s) -
Bo Li,
Tao Li,
Wenping Zhang,
Zijie Liu,
Yang Lei
Publication year - 2021
Publication title -
geofluids
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.44
H-Index - 56
eISSN - 1468-8123
pISSN - 1468-8115
DOI - 10.1155/2021/8812144
Subject(s) - inrush current , coal mining , mining engineering , analytic hierarchy process , coal , variable (mathematics) , computer science , evaluation methods , information fusion , data mining , environmental science , operations research , geology , engineering , artificial intelligence , mathematics , reliability engineering , waste management , mathematical analysis , voltage , electrical engineering , transformer
The use of multisource information fusion technology to predict the risk of water inrush from coal floor is a research hotspot in recent years, but the current evaluation method is mainly based on a constant weight evaluation model. Using constant weights to reflect the control effect of changing factor state values on water inrush evaluation has obvious limitations, and it is unable to describe the control effect of the hydrogeological condition mutation on the water inrush from the floor. In order to solve the above problems, this manuscript introduces the idea of variable weight into the field of water inrush evaluation, expounds on the significance of variable weight theory for water inrush evaluation, analyzes the characteristics of mine water inrush variable weight evaluation, and, on this basis, further combines GIS-based multisource information fusion technology and typical engineering case to compare with the evaluation effect map, evaluation unit, and comprehensive evaluation values. The differences between the variable weight model (VWM) and the constant weight model (CWM) are analyzed, which proves that the evaluation process of the variable weight evaluation model is more reasonable and can effectively improve the evaluation accuracy.

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