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Evaluation of Water-richness of Weathered Bedrock Based on the WOA-SVM Discriminant Model: Take Zhangjiamao Coal Mine in Shenfu Coal Field as an Example
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En-ke HOU1, Jia-mei WU1, *, Fan YANG2, Chi ZHANG2
Science Technology and Engineering | 2025, 25(1) : 119 - 127
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Science Technology and Engineering | 2025, 25(1): 119-127
Papers·Mining and Metallurgical Engineering
Evaluation of Water-richness of Weathered Bedrock Based on the WOA-SVM Discriminant Model: Take Zhangjiamao Coal Mine in Shenfu Coal Field as an Example
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En-ke HOU1, Jia-mei WU1, *, Fan YANG2, Chi ZHANG2
Affiliations
  • 1. College of Geology and Environment, Xi’an University of Science and Technology, Xi’an 710054, China
  • 2. Shenmu Zhangjiamao Mining Co., Ltd., Shaanxi Coal and Chemical Industry Group, Yulin 719316, China
Published: 2025-01-08 doi: 10.12404/j.issn.1671-1815.2401495
Outline
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In order to accurately predict the water richness of the weathered bedrock aquifer, 28 groups of weathered bedrock pumping test borehole data in Zhangjimao minefield were used as training and verification samples, and the lithology combination index, weathering index, thickness, core recovery rate and burial depth of the weathered bedrock were selected as evaluation indexes. Based on whale optimization algorithm-support vector machines (WOA-SVM), a water-rich identification model for weathering bedrock aquifers was proposed. This model can predict the water-rich grade of the weathered bedrock in the area without pumping test data, and realize water-rich zoning of the weathered bedrock in the well field by comprehensive use of the geological information of 249 exploration boreholes. The study shows that the weathered bedrock of Zhangjiamao minefield is weakly water-rich as a whole, and its spatial distribution is uneven. There are strong water-rich areas in the central part of the field and the local area along Wulanbula Gully, but their distribution range is small, there are some moderately water-rich areas in the central-western and southeastern parts, and the northeastern and southwestern areas are weakly and very weakly water-rich almost all the time. The results predicted are more in line with the actual situation, and the research results can provide a reference for the safe production of the mine and a new way of thinking for the prediction of the water-richness of the weathered bedrock.

weathered bedrock  /  support vector machine(SVM)  /  whale optimization algorithm (WOA)  /  water richness zoning
En-ke HOU, Jia-mei WU, Fan YANG, Chi ZHANG. Evaluation of Water-richness of Weathered Bedrock Based on the WOA-SVM Discriminant Model: Take Zhangjiamao Coal Mine in Shenfu Coal Field as an Example[J]. Science Technology and Engineering, 2025 , 25 (1) : 119 -127 . DOI: 10.12404/j.issn.1671-1815.2401495
Year 2025 volume 25 Issue 1
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Article Info
doi: 10.12404/j.issn.1671-1815.2401495
  • Receive Date:2024-03-05
  • Online Date:2025-07-29
  • Published:2025-01-08
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History
  • Received:2024-03-05
  • Revised:2024-10-09
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Affiliations
    1. College of Geology and Environment, Xi’an University of Science and Technology, Xi’an 710054, China
    2. Shenmu Zhangjiamao Mining Co., Ltd., Shaanxi Coal and Chemical Industry Group, Yulin 719316, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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