2020 Vol.3 Aug. No.4

• Title: Research on mining disaster factors of 3D geological structure based on big data technology
• Name: Jerry Chun-Wei Lin
• Company: Department of Computer Science, Electrical Engineering and Mathematical Sciences Western Norway University of Applied Sciences, Bergen, Norway
• Abstract:

  In order to solve the problem of low accuracy of traditional disaster factor mining and complex calculation process, a three-dimensional geological structure disaster factor mining based on big data technology is proposed to meet the ever-increasing safety requirements. Obtaining the area values corresponding to different geological structural hazard factors through big data technology, and using the certainty coefficient method to more intuitively analyze the types of key factors in the occurrence of three-dimensional geological structures, improving the accuracy of follow-up evaluation, according to geological factors, external induced factors and man-made factors establish an evaluation system and calculate the overall frequency between the average density of geological hazards of various index factor attributes. Through the probability numerical model and the information evaluation model, the sensitivity evaluation is divided into low sensitivity area, medium sensitivity area, high sensitivity area and extremely high sensitivity area. Experiments have proved that the evaluation model in this paper is easy to calculate with highly accurate, has strong rationality and applicability, and can be used as a basic scientific basis for three-dimensional geological structure related research and development planning.

  
  

• Keyword: Geological disasters; disaster factor; sensitivity evaluation; contribution rate
• DOI: 10.12250/jpciams2020040403
• Citation form: Jerry Chun-Wei Lin.Research on mining disaster factors of 3D geological structure based on big data technology[J]. Computer Informatization and Mechanical System, 2020, vol. 3, pp. 26-35.

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