Affiliations: [a] College of Safety and Emergency Management Engineering, Taiyuan University of Technology, Taiyuan, China
| [b] College of Mining, Liaoning Technical University, Fuxin, China
Correspondence:
[*]
Corresponding author. Jiaqi Yu, College of Mining Liaoning Technical University, Fuxin, China.
E-mail: [email protected].
Abstract: As there are many uncertain factors in the geological hazard risk, great challenges are brought to the comprehensive evaluation of it. In order to improve the comprehensiveness and accuracy of geological hazard risk assessment, a cloud fuzzy clustering algorithm is constructed in this paper, which can effectively estimate and evaluate uncertain variables. The weight value of the risk cloud droplets is calculated as the input. By setting up clustering conditions and function output conditions, the cluster weights of the inputs which meet requirements can be obtained by multiple clustering iterations. Through the introduction of time parameters, the influence of time factors on data importance and the risk severity of geological disaster emergencies are fully considered. The experimental results show that the calculated risk degree cluster weights are less than 1, which verifies the feasibility and practicability of the algorithm. The research in this paper shows that the clustering dynamic assessment of geological hazards can help to improve the accuracy of risk assessment and provide reference and help for the prevention and control of regional geological hazards.
