Overview of uncertainty assessment on karst collapse prediction

WAN Jiawei; ZHANG Qinjun; SHI Shujing

doi:10.11932/karst20170601

Volume 36 Issue 6

Dec. 2017

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WAN Jiawei, ZHANG Qinjun, SHI Shujing. Overview of uncertainty assessment on karst collapse prediction[J]. CARSOLOGICA SINICA, 2017, 36(6): 764-769. doi: 10.11932/karst20170601

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WAN Jiawei, ZHANG Qinjun, SHI Shujing. Overview of uncertainty assessment on karst collapse prediction[J]. CARSOLOGICA SINICA, 2017, 36(6): 764-769. doi: 10.11932/karst20170601

WAN Jiawei, ZHANG Qinjun, SHI Shujing. Overview of uncertainty assessment on karst collapse prediction[J]. CARSOLOGICA SINICA, 2017, 36(6): 764-769. doi: 10.11932/karst20170601

Citation:

WAN Jiawei, ZHANG Qinjun, SHI Shujing. Overview of uncertainty assessment on karst collapse prediction[J]. CARSOLOGICA SINICA, 2017, 36(6): 764-769. doi: 10.11932/karst20170601

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Overview of uncertainty assessment on karst collapse prediction

doi: 10.11932/karst20170601

Guangxi Zhuang Autonoumous Region Institute of Geology Survey

Publish Date: 2017-12-25

Abstract

Abstract

This paper reviews the development and the most recent progress of the uncertainty assessment on karst collapse prediction and summarizes the general approach of assessment. It is indicated that the assessment must be based on the geological background and actual condition in the evaluation area and the methodologyof "from qualitative to quantitative" should be followed. The general approach consists of 3 steps, including analyzing the influencing factors, selecting evaluation components and then constructing the evaluation model. This paper also elaborates on how to implement these steps. In this paper, comparative analysis on features, core steps, advantages, disadvantages among fuzzy model, grey-fuzzy model, information model, weights of evidence model, ANN model, SVM model are conducted,which provides a reference for model selection.Further more, it is pointed out that in the current uncertainty assessment on karst collapse prediction in China is very behind, which caused many problems in this field.
- karst collapse,
- uncertainty assessment,
- prediction,
- evaluation factor,
- evaluation model

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References(44)

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Overview of uncertainty assessment on karst collapse prediction

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