王飞, 王常明, 王冰, 丁桂伶. 2016: 基于模糊-集对分析理论的泥石流危险性评价. 工程地质学报, 24(s1): 817-822. DOI: 10.13544/j.cnki.jeg.2016.s1.118
    引用本文: 王飞, 王常明, 王冰, 丁桂伶. 2016: 基于模糊-集对分析理论的泥石流危险性评价. 工程地质学报, 24(s1): 817-822. DOI: 10.13544/j.cnki.jeg.2016.s1.118
    WANG Fei, WANG Changming, WANG Bing, DING Guiling. 2016: DEBRIS FLOW RISK DEGREE ASSESSMENT BASED ON FUZZY SET PAIR ANALYSIS. JOURNAL OF ENGINEERING GEOLOGY, 24(s1): 817-822. DOI: 10.13544/j.cnki.jeg.2016.s1.118
    Citation: WANG Fei, WANG Changming, WANG Bing, DING Guiling. 2016: DEBRIS FLOW RISK DEGREE ASSESSMENT BASED ON FUZZY SET PAIR ANALYSIS. JOURNAL OF ENGINEERING GEOLOGY, 24(s1): 817-822. DOI: 10.13544/j.cnki.jeg.2016.s1.118

    基于模糊-集对分析理论的泥石流危险性评价

    DEBRIS FLOW RISK DEGREE ASSESSMENT BASED ON FUZZY SET PAIR ANALYSIS

    • 摘要: 集对分析理论是一种处理确定性和不确定性的定量系统分析方法。本文通过模糊联系度对集对分析理论中的差异度系数做进一步挖掘和分析,建立了模糊-集对分析算法,即通过模糊联系度挖掘样本数据讨论类别与相邻类别间的接近程度,得出该类别与相邻类别之间的同异反信息。为了验证模型的适用性,通过实测北京房山区和门头沟区6条泥石流小流域基础数据,进行了危险性评价,并将评价结果与传统评价理论进行对比分析。得出结论:模糊-集对分析理论可以深度挖掘样本类别与相邻类别之间的同异反关系,通过对比现场调查数据发现模糊-集对分析法对泥石流小流域的评价结果更切合实际,且评价结果与可拓学等评价结果基本一致,该方法具有较高的准确性和严密性。

       

      Abstract: Set pair analysis theory(SPA) is a quantitative analysis method for dealing with uncertainty and uncertainty. In the paper, FSPA algorithm is established by using the fuzzy connection degree of the SPA to further explore and analyze the difference coefficient. The aim is to discuss the close degree between the class and the adjacent categories by using the fuzzy relation data mining, and to discuss similarity and difference information. In order to verify the applicability of the model, the risk assessment was carried out by measuring the basic data of six debris flows in Fangshan District and Mentougou area of Beijing, and the evaluation results were compared with the theory of extension theory. the study concluded that Fuzzy set pair analysis theory can depth mining similarities and differences between sample types and adjacent categories inverse relation. By comparing with the field survey data, It was found that FSPA evaluation results of information mining more realistic. The evaluation results of this method are consistent with the results of the extension evaluation. The method has high accuracy and precision.

       

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