Evaluation of Fire Emergency Capability for High-rise Residential Buildings based on Method of G1-Grey Clustering

Xinyue Liu ； Yang Li

《International Core Journal of Engineering》 8卷10期 (2022/10) Pp. 125-132

https://doi.org/10.6919/ICJE.202210_8(10).0019

摘要

In recent years, fire accidents in high-rise residential buildings have caused immeasurable losses. How to effectively reduce the fire occurrence and loss of high-rise residential buildings has become a concern of the whole society. Four aspects of fire prevention and emergency preparedness, monitoring and early warning, disposal capacity and recovery capacity are selected to establish the evaluation indexes system of fire emergency capacity of high-rise residential buildings. According to the characteristics of fire disaster in high-rise residential buildings, an evaluation method of fire emergency capacity of high-rise residential buildings based on G1-grey clustering method has been proposed. According to the grey whitening weight function, the evaluation information of fire emergency capacity of high-rise residential buildings is classified, the fire emergency capacity of high-rise residential buildings is analyzed by cluster analysis. Finally, the emergency capacity level is obtained. The evaluation model makes a scientific evaluation on the emergency capacity of high-rise residential buildings.

關鍵字

High-rise Residential Building ； Emergency Response Capability ； Grey Clustering ； G1 Method

參考文獻

Donderi, D. C. (2006). Visual complexity: a review. Psychological bulletin, 132(1), 73.

Leeuwenberg, E. L. (1969). Quantitative specification of information in sequential patterns. Psychological Review, 76(2), 216.

Simon, H. A. (1972). Complexity and the representation of patterned sequences of symbols. Psychological review, 79(5), 369.

Forsythe, A., Nadal, M., Sheehy, N., Cela‐Conde, C. J., & Sawey, M. (2011). Predicting beauty: Fractal dimension and visual complexity in art. British journal of psychology, 102(1), 49-70.

Marin, M. M., & Leder, H. (2013). Examining complexity across domains: relating subjective and objective measures of affective environmental scenes, paintings and music. PloS one, 8(8), e72412.