LAPSE:2023.35062
Published Article
LAPSE:2023.35062
Fuzzy Logic Regional Landslide Susceptibility Multi-Field Information Map Representation Analysis Method Constrained by Spatial Characteristics of Mining Factors in Mining Areas
Yongguo Zhang, Jin Zhang, Liang Dong
April 28, 2023
Abstract
Landslide susceptibility analysis has become a necessary means of pre-disaster portal positioning and scientific early warning. How can an effective zoning model of landslide susceptibility be established to examine the important factors affecting landslide development in coal mine areas? Focusing on the need for a reliability analysis of landslide susceptibility in coal mine areas, landslide cataloging and environmental factor data were used as objects, combined with the knowledge of landslide mechanisms, disaster environmental factors and the spatial correlation of landslide disasters, the frequent landslide area of Jiumine in the main part of Xishan Coalfield was selected as the research area, and more than 50 influencing factors were collected and calculated. Eighteen factors with correlation coefficients of less than 0.3 were selected, and a landslide susceptibility analysis method combining the spatial characteristics of landslide factors and the heuristic fuzzy logic model was proposed. The influence of the fuzzy logic model on the accuracy of landslide susceptibility analysis results under different constraint modes was tested. The model is a mixture of knowledge-driven and data-driven models, and is compared with information model and SVM. Experimental results show that the proposed method is feasible and reliable, and improves the accuracy of model results.
Keywords
fuzzy logic, information amount, knowledge-driven models, mining factor, multi-field information graph, SVM
Suggested Citation
Zhang Y, Zhang J, Dong L. Fuzzy Logic Regional Landslide Susceptibility Multi-Field Information Map Representation Analysis Method Constrained by Spatial Characteristics of Mining Factors in Mining Areas. (2023). LAPSE:2023.35062
Author Affiliations
Zhang Y: School of Mining Engineering, Taiyuan University of Technology, Taiyuan 030024, China
Zhang J: School of Mining Engineering, Taiyuan University of Technology, Taiyuan 030024, China
Dong L: School of Mining Engineering, Taiyuan University of Technology, Taiyuan 030024, China
Journal Name
Processes
Volume
11
Issue
4
First Page
985
Year
2023
Publication Date
2023-03-23
ISSN
2227-9717
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Original Submission
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PII: pr11040985, Publication Type: Journal Article
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LAPSE:2023.35062
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https://doi.org/10.3390/pr11040985
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