Risk assessment of fire safety in large-scale commercial and high-rise buildings based on intuitionistic fuzzy and social graph

Journal of Building Engineering(2024)

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摘要
Fire risk assessment is a useful method to identify potential fire risks and improve safety management, especially for those large-scale commercial and high-rise buildings. However, after the establishment of the fire risk indexing system, the weight assignment in the existing assessment methods is not scientific and objective enough to synthesize the opinions of multiple experts with different knowledge backgrounds and working experience. To solve this problem, a novel fire risk assessment for large-scale commercial and high-rise buildings is proposed with intuitionistic fuzzy and social graph. First, based on the national standards of fire safety management, the monthly maintenance and the annual fire assessment reports, the indexing system is established. Then, a scientific and objective weight assignment method called Social Graph based Intuitionistic Fuzzy Analytic Hierarchy Process (SGIFAHP) is proposed such that (1) by utilizing the Intuitionistic Fuzzy and social graph, it can synthesize the positive, negative and hesitant opinions from multiple experts by considering the importance of experts; (2) a novel mechanism is designed to automatically check and repair the consistency of the opinions of each expert when the expert compares the importance of risk factors. To validate the performance of the proposed method, eleven buildings are selected and their fire safety data are collected. A comparison analysis is carried out with the existing methods to compare the assigned weights. The comparison and score validation conclude that the proposed method can assign more reasonable, scientific and objective weights than the existing methods while the scores are comprehensive and strongly interpretable. In the end, a guide is offered to help safety owners and inspectors improve fire safety with the proposed method.
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关键词
Risk assessment,Social graph,Intuitionistic fuzzy,Fire safety
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