Cao Chen, Xu Peihua, Chen Jianping, Zheng Lianjing, Niu Cencen
College of Construction Engineering, Jilin University, Changchun 130026, China.
Construction Engineering College, Changchun Sci-Tech University, Changchun 130600, China.
Int J Environ Res Public Health. 2016 Dec 29;14(1):30. doi: 10.3390/ijerph14010030.
This study focused on a cloud model approach for considering debris-flow hazard assessment, in which the cloud model provided a model for transforming the qualitative and quantitative expressions. Additionally, the entropy method and analytical hierarchy process were united for calculating the parameters weights. The weighting method avoids the disadvantages inherent in using subjective or objective methods alone. Based on the cloud model and component weighting method, a model was established for the analysis of debris-flow hazard assessment. There are 29 debris-flow catchments around the pumped storage power station in the study area located near Zhirui (Inner Mongolia, China). Field survey data and 3S technologies were used for data collection. The results of the cloud model calculation process showed that of the 29 catchments, 25 had low debris-flow hazard assessment, three had moderate hazard assessment, and one had high hazard assessment. The widely used extenics method and field geological surveys were used to validate the proposed approach. This approach shows high potential as a useful tool for debris-flow hazard assessment analysis. Compared with other prediction methods, it avoids the randomness and fuzziness in uncertainty problems, and its prediction results are considered reasonable.
本研究聚焦于一种用于泥石流灾害评估的云模型方法，其中云模型提供了一种用于转换定性和定量表达的模型。此外，将熵权法和层次分析法结合起来计算参数权重。这种加权方法避免了单独使用主观或客观方法所固有的缺点。基于云模型和分量加权法，建立了一个用于泥石流灾害评估分析的模型。研究区域位于中国内蒙古自治区智瑞附近的抽水蓄能电站周边有29个泥石流流域。利用实地调查数据和3S技术进行数据收集。云模型计算过程的结果表明，在这29个流域中，25个泥石流灾害评估为低，3个为中等灾害评估，1个为高灾害评估。采用广泛使用的可拓学方法和实地地质调查对所提出的方法进行验证。该方法作为泥石流灾害评估分析的有用工具具有很大潜力。与其他预测方法相比，它避免了不确定性问题中的随机性和模糊性，其预测结果被认为是合理的。
