Risk Evaluation for Bridge Engineering Based on Cloud-Clustering Group Decision Method

Abstract

A combined analytic hierarchy process (AHP) method, Delphi method, and cloud model, i.e., a cloud clustering–based group decision method, is proposed. The risk probability and risk loss of the main risk factors are scored by experts. A backward cloud generator is used to calculate the digital characteristics of the sample from the experts’ scoring. A forward cloud generator is used to generate the cloud droplets according to the scoring samples from the experts. An iteration method is approved to quantify the coherence. Introduction of the expert authority, group decision risk probability, and risk loss can be obtained based on the cloud model. Similarly, the group decision weight of risk resources can also be obtained by the cloud-clustering group decision method. According to the risk resource weight, risk probability, and risk loss, risk level can be determined based on the risk judgment matrix. The study results show that the risk level of the example cable-stayed bridge is Level II, which is very similar to the computation achieved by a method derived from the current safety risk assessment guide in China. However, cloud clustering can ensure higher coherence for the samples. Consequently, the risk evaluation result will be more stable. The real bridge example and comparison analysis show that the cloud-clustering group decision method is reasonable and can objectively estimate the bridge risk.