Electrical fire risk assessment of high‐rise buildings based on hybrid decision model considering asymmetric proximity

Abstract At present, there are some problems in the research of electrical fire risk assessment of high‐rise buildings, such as the evaluation index is relatively single and the fuzziness of evaluation state boundary is not considered. This study proposed an electrical fire risk assessment method of high‐rise buildings based on hybrid decision model considering asymmetric proximity. Based on the occurrence mechanism of electrical fire in high‐rise buildings, a four‐level evaluation index system considering disaster causing body, fire site environment, affected body and fire driving factors is established based on FP growth (Frequent Pattern Tree Growth) mining association rules, and the risk grade is divided further. An improved index weight assignment method for balancing the interaction relationship between indexes is proposed, and a hybrid decision‐making model for electrical fire risk assessment of high‐rise buildings is established. Combined with specific examples, the effectiveness of the proposed building electrical fire risk assessment method is verified. The weight standard deviation of the proposed method is 0.0464, which is about 13.8% smaller than that of analytic hierarchy process (0.0528). So the method can better balance each risk evaluation index, fully consider the fuzziness and randomness in the electrical fire risk assessment of high‐rise buildings, and improve the accuracy and applicability of electrical fire risk assessment.