LAPSE:2024.0715
Published Article
LAPSE:2024.0715
Novel Method on Mixing Degree Quantification of Mine Water Sources: A Case Study
June 6, 2024
After a mine water inrush occurs, it is crucial to quickly identify the source of the water inrush and the key control area, and to formulate accurately efficient water control measures. According to the differences in water chemical characteristics of four aquifers in the Fenyuan coal mine, the concentrations of K+~Na+, Ca2+, Mg2+, Cl−, SO42−, and HCO3− were taken as water source identification indexes. A decision tree classification model based on the C4.5 algorithm was adopted to visualize the chemical characteristics of a single water source and extract rules, and intuitively obtained the discrimination conditions of a single water source with Mg2+, Ca2+, and Cl− as important variables in the decision tree: Mg2+ < 39.585 mg/L, Cl− < 516.338 mg/L and Mg2+ ≥ 39.585 mg/L, Ca2+ < 160.860 mg/L. Factor analysis and Fisher discriminant theory were used to eliminate the redundant ion variables, and the discriminant function equations of the two, three, and four types of mixed water sources were obtained successively in turn. This paper puts forward MSE, RMSE, and MAE as the evaluation indexes of the water source mixing degree calculation models and obtains the ranking of the pros and cons of the mixed water source mixing degree calculation models. The results show that the minimum inscribed circle analytical method is the optimal model for the calculation of the mixing degree of two types of water sources, and the MSE, RMSE, and MAE are 0.17%, 4.13%, and 4.13%, respectively. The minimum inscribed circle clustering method is the optimal model for the calculation of the mixing degree of three types of water sources, and the minimum distance method is the optimal model for the calculation of the mixing degree of four types of water sources. The method of mine water source identification based on the decision tree C4.5 algorithm and mixing degree calculation has the characteristics of a simple calculation process, high efficiency, objective accuracy, and low cost, which can provide a scientific basis for the development of stope water control measures.
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Keywords
decision tree, discriminant function equation, mine water inrush source, mixing degree of water sources
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Suggested Citation
Li Q, Fan G, Zhang D, Yu W, Zhang S, Fan Z, Fu Y. Novel Method on Mixing Degree Quantification of Mine Water Sources: A Case Study. (2024). LAPSE:2024.0715
Author Affiliations
Li Q: School of Mines, China University of Mining and Technology, Xuzhou 221116, China; State Key Laboratory of Coal Resources and Mine Safety, Xuzhou 221116, China
Fan G: School of Mines, China University of Mining and Technology, Xuzhou 221116, China; State Key Laboratory of Coal Resources and Mine Safety, Xuzhou 221116, China [ORCID]
Zhang D: School of Mines, China University of Mining and Technology, Xuzhou 221116, China; State Key Laboratory of Coal Resources and Mine Safety, Xuzhou 221116, China
Yu W: School of Mines, China University of Mining and Technology, Xuzhou 221116, China; State Key Laboratory of Coal Resources and Mine Safety, Xuzhou 221116, China
Zhang S: School of Mines, China University of Mining and Technology, Xuzhou 221116, China; State Key Laboratory of Coal Resources and Mine Safety, Xuzhou 221116, China
Fan Z: School of Mines, China University of Mining and Technology, Xuzhou 221116, China; State Key Laboratory of Coal Resources and Mine Safety, Xuzhou 221116, China
Fu Y: School of Civil Engineering, Harbin Institute of Technology, Harbin 150006, China
Fan G: School of Mines, China University of Mining and Technology, Xuzhou 221116, China; State Key Laboratory of Coal Resources and Mine Safety, Xuzhou 221116, China [ORCID]
Zhang D: School of Mines, China University of Mining and Technology, Xuzhou 221116, China; State Key Laboratory of Coal Resources and Mine Safety, Xuzhou 221116, China
Yu W: School of Mines, China University of Mining and Technology, Xuzhou 221116, China; State Key Laboratory of Coal Resources and Mine Safety, Xuzhou 221116, China
Zhang S: School of Mines, China University of Mining and Technology, Xuzhou 221116, China; State Key Laboratory of Coal Resources and Mine Safety, Xuzhou 221116, China
Fan Z: School of Mines, China University of Mining and Technology, Xuzhou 221116, China; State Key Laboratory of Coal Resources and Mine Safety, Xuzhou 221116, China
Fu Y: School of Civil Engineering, Harbin Institute of Technology, Harbin 150006, China
Journal Name
Processes
Volume
12
Issue
3
First Page
438
Year
2024
Publication Date
2024-02-21
ISSN
2227-9717
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PII: pr12030438, Publication Type: Journal Article
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LAPSE:2024.0715
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https://doi.org/10.3390/pr12030438
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Jun 6, 2024
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