Risk Evaluation of Debris Flow Hazard Based on Asymmetric Connection Cloud Model

Xinyu Xu,Libiao Zhang,Yafeng Li,Mingwu Wang

doi:10.1155/2017/5348149

Xinyu Xu, Libiao Zhang + Show 2 more

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https://doi.org/10.1155/2017/5348149

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Abstract

Risk assessment of debris flow is a complex problem involving various uncertainty factors. Herein, a novel asymmetric cloud model coupled with connection number was described here to take into account the fuzziness and conversion situation of classification boundary and interval nature of evaluation indicators for risk assessment of debris flow hazard. In the model, according to the classification standard, the interval lengths of each indicator were first specified to determine the digital characteristic of connection cloud at different levels. Then the asymmetric connection clouds in finite intervals were simulated to analyze the certainty degree of measured indicator to each evaluation standard. Next, the integrated certainty degree to each grade was calculated with corresponding indicator weight, and the risk grade of debris flow was determined by the maximum integrated certainty degree. Finally, a case study and comparison with other methods were conducted to confirm the reliability and validity of the proposed model. The result shows that this model overcomes the defect of the conventional cloud model and also converts the infinite interval of indicators distribution into finite interval, which makes the evaluation result more reasonable.

Highlights

Debris flow is a common natural hazard that frequently appears in the mountainous region of southwestern China, such as Gongshan district and Dongchuan district in Yunnan province, and Ridigou district in Sichuan province
The newly developed cloud model theory shows its advantage in dealing with the uncertainty problems [10]; the certainty degree of the measured sample to classification grades is generated automatically by the special algorithm, which avoids the defect of determining the certainty degree subjectively and considers the fuzziness and randomness of evaluation indicators as a whole and achieves the qualitative and quantitative conversion, so it provides a new idea for assessment risk of debris flow
There are two types of evaluation indicators; for the first type of indicator which is defined for maximum – optimum index, corresponding lengths of left half-interval and right half-interval are given as ai−L = Exi − Lim−1in, (11)

Summary

Introduction

Debris flow is a common natural hazard that frequently appears in the mountainous region of southwestern China, such as Gongshan district and Dongchuan district in Yunnan province, and Ridigou district in Sichuan province. Researchers endeavored to present various methods for the rational prediction of debris flow, such as grey relational analysis method [3], extension method [4, 5], fuzzy comprehensive evaluation method [6], and BP neural network method [7], and obtained many useful results. The mapping approach which used GIS technology might be arbitrarily different in the discrete risk assessment of debris flow system Overall, whereas these researches have advanced the risk assessment of debris flow, it Mathematical Problems in Engineering is still not well resolved nowadays since debris flow evaluation involves various uncertainty influence factors. There is an obvious defect in the conventional cloud model that indicators must obey normal distribution and locate in infinite interval; this is not always in accordance with the actual indicators distribution, which inevitably limits its application

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Results

Conclusion