Citation

Hu J, Shu X, Shen S, Yan J, Tian F, He S, Ni X. Fire Mater. 2022; 46(4): 666-676.

Copyright

(Copyright © 2022, John Wiley and Sons)

DOI

10.1002/fam.3014

PMID

unavailable

Abstract

The traditional research of building fire probability analysis is from statistics or fire science. This paper combines the two methods and aims to improve the statistical method of building ignition probability determination according to the research conclusion of fire science. The specific factors that affect the ignition probability are divided into three aspects: humans, ignition sources and combustibles and environments. On this basis, the Bayesian network of building ignition probability is constructed, the nodes and conditional probability table in the Bayesian network are introduced in detail, according to which the ignition probability of building can be calculated quantitatively and objectively. Then some typical buildings are chosen as examples for the application of the method, the posterior probability value is calculated by obtaining the relevant building information and substituting them into the Bayesian network. The ignition probability is dynamic, and the comparison with the statistical data of building fire also proves its rationality.

Language: en

Keywords

Bayesian network; building fires; dynamic probability; ignition probability; posterior probability