Regional High-Rise Building Fire Risk Assessment Based on the Spatial Markov Chain Model and an Indicator System

作者：Yan Zhang, Guru Wang, Xuehui Wang, Xin Kong, Hongchen Jia, Jinlong Zhao · 发表于：Fire · 年份：2024 · DOI：10.3390/fire7010016 · 被引用次数：14 · 研究领域：Evacuation and Crowd Dynamics、Urban Transport and Accessibility、Urban Green Space and Health

High-rise buildings (HRBs) are prone to high fire hazards due to their high occupant density, limited evacuation routes, and high fire load. The indicator system method, as a systematic evaluation method, is widely applied to assess HRB fire risk. However, the method is subjective because the determination of the indicator weights mainly relies on expert experience. In order to reduce the subjectivity of the indicator system method in assessing the fire risk of HRBs, this study proposes a new assessment method by combining the spatial Markov chain model and the indicator system method. In this new method, fire occurrence probability is calculated by the spatial Markov chain model using historical HRB fire accident data. An indicator system is built to characterize the fire consequence by the structure entropy weight method. Subsequently, HRBs in Beijing are used as a case to illustrate the practicality of this approach. Firstly, the spatial Markov chain model is trained and validated using the chi-square goodness-of-fit test based on fire accident data from 2018 to 2023 in Beijing. It was found that the best performance was achieved with the monthly period and the four-state. Then, the distribution of regional fire occurrence probability in April was predicted based on fire accident data in March 2023 in Beijing. It showed that areas with higher fire occurrence probability are mainly located in the central region, especially in the I District. Then, the indicator system was u...