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Modelling dwelling fire development and occupancy escape using Bayesian network
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AI
DOI：10.1016/j.ress.2013.01.001.png)
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Abstract
En 中文
The concept of probabilistic modelling under uncertainty within the context of fire and rescue through the application of the Bayesian network (BN) technique is presented in this paper. BNs are capable of dealing with uncertainty in data, a common issue within fire incidents, and can be adapted to represent various fire scenarios. A BN model has been built to study fire development within generic dwellings up to an advanced fire situation. The model is presented in two parts: part I deals with initial fire development and part II occupant response and further fire development. Likelihoods are assessed for states of human reaction, fire growth, and occupant survival. Case studies demonstrate how the model functions and provide evidence that it could be used for safety assessment, planning and accident investigation. Discussion is undertaken on how the model could be further developed to investigate specific areas of interest affecting dwelling fire outcomes. (C) 2013 Elsevier Ltd. All rights reserved.
Keywords:
Bayesian network
Dwellings
Human reaction
Fire growth/flashover
State of the occupant
Journal
R
IF:
11
Papers:
9.0K
Citations:
4.2W