Modelling dwelling fire development and occupancy escape using Bayesian network
نویسندگان
چکیده
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. & 2013 Elsevier Ltd. All rights reserved.
منابع مشابه
A Spatio-temporal Probabilistic Model of Hazard and Crowd Dynamics in Disasters for Evacuation Planning
Managing the uncertainties that arise in disasters – such as ship fire – can be extremely challenging. Previous work has typically focused either on modeling crowd behavior or hazard dynamics, targeting fully known environments. However, when a disaster strikes, uncertainty about the nature, extent and further development of the hazard is the rule rather than the exception. Additionally, crowd ...
متن کاملAssessment of Critical Fire Risks in an Industrial Estate Using a Combination of Fuzzy Logic, Expert Elicitation, Bow-tie, and Monte Carlo Methods
Background and Objective: Industrial estates have been described as highly prone to fire incidents. According to the baseline studies, more than 85% of the industrial accidents occurring in industrial estates during the 80s and 90s were fire incidents affecting more than one factory in 10% of the cases. Materials and Methods: After the identification of 30 high-risk industries in Abbasabad i...
متن کاملImprove Estimation and Operation of Optimal Power Flow(OPF) Using Bayesian Neural Network
The future of development and design is impossible without study of Power Flow(PF), exigency the system outcomes load growth, necessity add generators, transformers and power lines in power system. The urgency for Optimal Power Flow (OPF) studies, in addition to the items listed for the PF and in order to achieve the objective functions. In this paper has been used cost of generator fuel, acti...
متن کاملA Bayesian model decision support system: dryland salinity management application
Addressing environmental management problems at catchment scales requires an integrated modelling approach, in which key bio-physical and socio-economic drivers, processes and impacts are all considered. Development of Decision Support Systems (DSSs) for environmental management is rapidly progressing. This paper describes the integration of physical, ecological, and socio-economic components i...
متن کاملA State-Transition DBN for Management of Willows in an American Heritage River Catchment
Expansion of willows in the naturally mixed landscape of vegetation types in the Upper St. Johns River Basin in Florida, USA, impacts upon biodiversity, aesthetic and recreational values. Managers need an integrated knowledge base to support decisions on where, when and how to control willows. Modelling the spread of willows over space and time requires spatially explicit data on willow occupan...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Rel. Eng. & Sys. Safety
دوره 114 شماره
صفحات -
تاریخ انتشار 2013