A MCMEIF-LT model for risk assessment based on linguistic terms and risk attitudes
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A MCMEIF-LT model for risk assessment based on linguistic terms and risk attitudes Donghong Tian1
· Chao Min1,2 · Lingna Li1 · Jie Gao1
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Due to the limitation of assessors’ knowledge and the uncertainty of risks, risk assessment data reasonably are given in the form of linguistic terms, safety risk assessment in petrochemical industry is often a multi-criterion and multi-expert information fusion based on linguistic terms(MCMEIF-LT) problem. A novel model dealing with the MCMEIF-LT problem is presented in this paper. Firstly, the individual linguistic assessment distributions are fused to collective distributions and multiple criteria are fused to a comprehensive criterion. In the fusion process, the objective weights of assessment experts are calculated with using the credibilities of assessment data and the attitudes of decision makers are considered. Secondly, a Fuzzy Number Weighted Ordered Weighted Aggregation(FN-WOWA) operator which can transform a fuzzy number into a crisp value is proposed. In the FN-WOWA operator, the utility function can incorporate the assessors’ loss-based risk attitudes and the membership function can reflect the importance of the values in the integrated fuzzy number. Based on crisp values, a risk matrix is constructed. Finally, a real application is demonstrated to show the flexibility and practicality of the MCMEIF-LT model. Keywords Risk assessment · Risk matrix · Information fusion · Risk attitudes · Linguistic terms · Fuzzy numbers
1 Introduction Petrochemical industry has become a high-risk industry. High temperature, inflammability, toxicant, high pressure, easy corrosion etc. all are the factors that possibly cause safety accidents. Countless safety accidents tell us that controlling safety risks in petrochemical industry is very issue. To control safety risks, assessing risks reasonably is the first and important work. According to the existing literatures [1–6], most scholars agree with that risk is a combination of frequency and consequence. Most risk assessment problems are carried out based on the two criteria. The frequency can be reflected by the time waiting for a risk happening once. The consequence in petrochemical industry mainly refers to losses and performs in several aspects, such as: accident level, direct Donghong Tian
[email protected] 1
School of Sciences, Southwest Petroleum University, Chengdu, China
2
Institute for Artificial Intelligence, Southwest Petroleum University, Chengdu, China
economic loss, reputation loss, and environmental pollution et al [5–9]. In general, there are mainly three ways to perform a risk assessment: quantitative way, semi-quantitative way, and qualitative way [1]. In most petrochemical enter-prises, some criteria(such as: reputation loss and environmental pollution) are not easily measured with money and some records of safety accidents are often missing. In this situation, Expert Scoring Method(ESM) is usually adopted to collect assessment
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