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

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Xinyu Xu ◽  
Mingwu Wang ◽  
Yafeng Li ◽  
Libiao Zhang
Keyword(s):  
Risk Assessment ◽  
Debris Flow ◽  
Cloud Model ◽  
Reliability And Validity ◽  
Complex Problem ◽  
Evaluation Standard ◽  
Classification Boundary ◽  
Asymmetric Connection ◽  
Interval Lengths ◽  
Debris Flow Hazard

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.

Risk Assessment of 2011 Debris Flow Hazard Area in Yongin City

2015 ◽  
Vol 15 (2) ◽  
pp. 165-178
Author(s):  
Gou-moon Choi ◽  
Seung Woo Lee ◽  
Chan-Young Yune
Keyword(s):  
Risk Assessment ◽  
Debris Flow ◽  
Hazard Area ◽  
Debris Flow Hazard

scholarly journals The Risk Assessment of Debris Flow Hazards in Banshanmen Gully Based on the Entropy Weight-Normal Cloud Method

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
X. B. Gu ◽  
S. T. Wu ◽  
X. J. Ji ◽  
Y. H. Zhu
Keyword(s):  
Risk Assessment ◽  
Debris Flow ◽  
Cloud Model ◽  
Risk Estimation ◽  
Assessment Method ◽  
Risk Level ◽  
Entropy Weight ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Index Weight

The debris flow is one of the geological hazards; its occurrence is complex, fuzzy, and random. And it is affected by many indices; a new multi-index assessment method is proposed to analyze the risk level of debris flow based on the entropy weight-normal cloud model in Banshanmen gully. The index weight is calculated by using the entropy weight method. Then, the certainty degree of each index belonging to the corresponding cloud is obtained by using the cloud model. The final risk level of debris flow is determined according to the synthetic certainty degree. The conclusions are drawn that the method is feasible and accurate rate of risk estimation for debris flow is very high, so a new method and thoughts for the risk assessment of debris flow can be provided in the future.

Methods for Debris Flow Hazard and Risk Assessment

2013 ◽  
pp. 133-177 ◽  
Author(s):  
Byron Quan Luna ◽  
Jan Blahut ◽  
Mélanie Kappes ◽  
Sami Oguzhan Akbas ◽  
Jean-Philippe Malet ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Debris Flow ◽  
Hazard And Risk ◽  
Hazard And Risk Assessment ◽  
Debris Flow Hazard

scholarly journals Multidimensional Connection Cloud Model Coupled with Improved CRITIC Method for Evaluation of Eutrophic Water

2022 ◽  
Vol 2022 ◽  
pp. 1-12
Author(s):  
Daguo Wu ◽  
Jiahui Yan ◽  
Mingwu Wang ◽  
Guangyao Chen ◽  
Juliang Jin ◽  
...  
Keyword(s):  
Cloud Model ◽  
Water Environment ◽  
Correlation Method ◽  
Evaluation Standard ◽  
Connection Degree ◽  
Appropriate Treatment ◽  
Proposed Model ◽  
Eutrophic Water ◽  
Classification Boundary ◽  
Criteria Importance

The degree of eutrophication in the water environment is deepening. For the appropriate treatment of eutrophication, it is essential to evaluate it accurately. However, the evaluation of eutrophication has not been well solved because it is full of uncertainty. Herein, a multidimensional connection cloud model, combined with the improved CRITIC (Criteria Importance Through Inter-criteria Correlation) method, was put forward here to assess water eutrophication and depict the randomness, ambiguity, and interaction of evaluation factors. First, an improved CRITIC was adopted to determine indicator weight so that the correlation among different indicators and more information were depicted. Secondly, a multidimensional connection cloud was simulated to characterize fuzzy indicators and ambiguous classification boundary values according to classification criteria. Next, the connection degree was calculated relative to the evaluation standard. The eutrophication grade was specified under the “maximum connection degree” principle. At last, the effectiveness and practicality of the model proposed here were affirmed by two cases and comparisons with supplementary methods. The results suggest that the proposed model can avoid shortcomings of the original CRITIC method and cloud model, and make the assessment result more realistic.

scholarly journals Quantitative Risk Assessment for Deep Tunnel Failure Based on Normal Cloud Model: A Case Study at the ASHELE Copper Mine, China

2021 ◽  
Vol 11 (11) ◽  
pp. 5208
Author(s):  
Jianpo Liu ◽  
Hongxu Shi ◽  
Ren Wang ◽  
Yingtao Si ◽  
Dengcheng Wei ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Large Scale ◽  
Cloud Model ◽  
Quantitative Risk Assessment ◽  
Geological Condition ◽  
Deep Tunnel ◽  
Entropy Weight ◽  
Copper Mine ◽  
Evaluation Indexes ◽  
Metal Mines

The spatial and temporal distribution of tunnel failure is very complex due to geologic heterogeneity and variability in both mining processes and tunnel arrangement in deep metal mines. In this paper, the quantitative risk assessment for deep tunnel failure was performed using a normal cloud model at the Ashele copper mine, China. This was completed by considering the evaluation indexes of geological condition, mining process, and microseismic data. A weighted distribution of evaluation indexes was determined by implementation of an entropy weight method to reveal the primary parameters controlling tunnel failure. Additionally, the damage levels of the tunnel were quantitatively assigned by computing the degree of membership that different damage levels had, based on the expectation normalization method. The methods of maximum membership principle, comprehensive evaluation value, and fuzzy entropy were considered to determine the tunnel damage levels and risk of occurrence. The application of this method at the Ashele copper mine demonstrates that it meets the requirement of risk assessment for deep tunnel failure and can provide a basis for large-scale regional tunnel failure control in deep metal mines.

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