scholarly journals Risk assessment of geological disasters in Nyingchi, Tibet

2021 ◽  
Vol 13 (1) ◽  
pp. 219-232
Author(s):  
Chenshuang Wu ◽  
Yonggang Guo ◽  
Libin Su
Keyword(s):  
Risk Assessment ◽  
Analytic Hierarchy Process ◽  
Reference Value ◽  
Fuzzy Analytic Hierarchy Process ◽  
Analytic Hierarchy ◽  
Geological Disasters ◽  
Ecological Protection ◽  
Highly Correlated ◽  
Landslides And Debris Flows ◽  
Hierarchy Process

Abstract To reduce the adverse effects of geological disasters on Nyingchi, this article selected nine highly correlated risk assessment factors for the types of geological disasters such as landslides and debris flows and used two methods of analytic hierarchy process and fuzzy analytic hierarchy process for analysis and comparison. The spatial overlay analysis of each factor with weight is carried out in ArcGIS to make a classification map of geological hazards in Nyingchi. Risk assessment of geological disasters such as collapses, landslides, and mudslides indicates that the slope, distance from the faults, and relative elevation difference of topography have severe impact on natural disasters; at least more than 60% of the areas belong to medium-, high-, and extremely high-risk areas, and it is urgent to strengthen protection and governance; the evaluation results of the fuzzy analytic hierarchy process are more in line with the actual survey situation and are more suitable for Tibet. This research is able to provide a basis for ecological protection, ecological restoration, and geological disaster prevention and management in southeastern Tibet. It also has important reference value for the coordinated development of urban and the environmental projects.

scholarly journals An Application of Fuzzy Analytic Hierarchy Process in Risk Evaluation Model

2021 ◽  
Vol 12 ◽  
Author(s):  
Geng Peng ◽  
Lu Han ◽  
Zeyan Liu ◽  
Yanyang Guo ◽  
Junai Yan ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Analytic Hierarchy Process ◽  
Evaluation Model ◽  
Fuzzy Analytic Hierarchy Process ◽  
Analytic Hierarchy ◽  
Land Conflicts ◽  
System A ◽  
Medium Level ◽  
Hierarchy Process ◽  
Controllability Index

Conflicts in land exploration are incisive social problems which have been the subject in many studies. Risk assessment of land conflicts is effective to resolve such problems. Specifically, fuzzy mathematics and the analytic hierarchy process were combined together to evaluate risk in land conflicts in our work, which is proved useful to solve uncertainty and imprecision problems. Based on the analysis of the principles for the risk assessment of a land conflicts index system, a set of risk assessment indexes using the fuzzy analytic hierarchy process (FAHP) was presented. The results show that the overall risk is at medium level, and the risk of the feasibility index and controllability index need to be paid more attention to. The contribution of this article is reflected in two aspects: (1) the application of FAHP in risk assessments of land conflicts is effective and valid; (2) it is helpful for governments to establish a stricter management system of work safety for conflicts in land exploration based on the risk assessment results.

The Application of Fuzzy Analytic Hierarchy Process Method and Artificial Neural Network Model in the Elevator Risk Assessment

2014 ◽  
Vol 1014 ◽  
pp. 552-555
Author(s):  
Xin Shi Li ◽  
You Cai Xu ◽  
Ran Tao ◽  
Shu Guo ◽  
Kun Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Risk Assessment ◽  
Artificial Neural Network ◽  
Analytic Hierarchy Process ◽  
Assessment Model ◽  
Fuzzy Analytic Hierarchy Process ◽  
Risk Assessment Model ◽  
Analytic Hierarchy ◽  
Artificial Neural ◽  
Hierarchy Process

The tradition elevator risk assessment model depends on the expert experience, which causes that the assessment process takes a long time. To deal with this problem, this paper proposes a new risk assessment model which is based on fuzzy analytic hierarchy process (F-AHP) and artificial neural network (ANN). This model is applied to the risk-assessment of elevators. The results show that the assessment time is shorter and the accuracy is not lower, in comparison with the traditional model.

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