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岩溶塌陷不确定性预测评价综述
引用本文:万佳威,张勤军,石树静. 岩溶塌陷不确定性预测评价综述[J]. 中国岩溶, 2017, 36(6): 764-769. DOI: 10.11932/karst20170601
作者姓名:万佳威  张勤军  石树静
作者单位:广西壮族自治区地质调查院
基金项目:中国地质调查局项目(12120114022101,12120115047401);中国地质调查项目(DD20160254)
摘    要:文章梳理了岩溶塌陷不确定性预测评价的发展历程和最新进展,总结形成了预测评价的一般思路,认为评价时应立足于评价区的地质背景和实际塌陷情况,遵守从定性到定量的原则,按照评价区实际情况,依次完成影响因素分析、评价因子选取、评价模型构建3个步骤,并对如何完成好这3个步骤进行了详细阐述;还针对常用的模糊综合评价模型、灰色模糊综合评判模型、信息量模型、证据权模型、人工神经网络模型、支持向量机模型,在特点、核心步骤、优势、弊端4个方面进行了分类对比分析。文章认为目前国内的岩溶塌陷不确定性预测评价还存在较大滞后,仍有许多问题亟待解决。

关 键 词:岩溶塌陷   不确定性   预测评价   评价因子   评价模型

Overview of uncertainty assessment on karst collapse prediction
WAN Jiawei,ZHANG Qinjun and SHI Shujing. Overview of uncertainty assessment on karst collapse prediction[J]. Carsologica Sinica, 2017, 36(6): 764-769. DOI: 10.11932/karst20170601
Authors:WAN Jiawei  ZHANG Qinjun  SHI Shujing
Affiliation:Guangxi Zhuang Autonoumous Region Institute of Geology Survey
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.
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