Citation

Shen L, Tang Y, Mu Y. China Saf. Sci. J. 2019; 29(10): 147-153.

Copyright

(Copyright © 2019, China Occupational Safety and Health Association, Publisher Gai Xue bao)

DOI

10.16265/j.cnki.issn1003-3033.2019.10.023

PMID

unavailable

Abstract

In order to reduce accident rates of component hoisting construction of prefabricated residence, a risk assessment model based on Cloud-BN was constructed to dynamically evaluate these risks. Firstly, feasibility and rationality of the combination of cloud model and Bayesian networks (BN) were analyzed. Secondly, risk index system and BN structure of component hoisting construction were established according to engineering practice, and conditional probability distribution among nodes was obtained through parameter learning algorithm. Then, the obtained prior probability was input into the model through cloud model transformation to reason out risk possibilities at various risk states before final risk levels were obtain through comprehensive cloud generation method. Finally, a prefabricated residence project was taken as an example to verify this model's effectiveness and advantages. It is proved that its results are basically consistent with reality with an average relative error rate within 5%, which is more objective and accurate compared with conventional BN models. © 2019 China Safety Science Journal. All rights reserved.

Language: zh