2019
DOI: 10.1016/j.firesaf.2019.05.002
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New approaches to evacuation modelling for fire safety engineering applications

Abstract: This paper presents the findings of the workshop "New approaches to evacuation modelling", which took place on the 11 th of June 2017 in Lund (Sweden) within the Symposium of the International Association for Fire Safety Science (IAFSS). The workshop gathered international experts in the field of fire evacuation modelling from 19 different countries and was designed to build a dialogue between the fire evacuation modelling world and experts in areas outside of fire safety engineering. The contribution to fire … Show more

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Cited by 32 publications
(4 citation statements)
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“…In addition to facilitating the control of the greenhouse microstructure, Recurrent LSTM Neural Network (R-LSTM-NN) and Deep Belief Network (DBN) (Batov, 2015;Raza and Khosravi, 2015;Lokshina et al, 2019;Zhang K. et al, 2021) have been proven useful in real-life fire hazard prevention and hazard warning (Bu and Gharajeh, 2019). genetic algorithm (GA), and adaptive neuro-fuzzy-inferencesystem (ANFIS), and artificial neural network (ANN), have been proven useful in similar applications (Arabasadi et al, 2013;Naser, 2019;Ronchi et al, 2019) and ecological monitoring (Molinara et al, 2021) using vision-based sensors (Bu and Gharajeh, 2019). The real-life applications would be augmented by robust R&D.…”
Section: Potential Solutions: Polymer Electrolyte Membrane Fuel Cell Stacks Double Skin Facades and Annsmentioning
confidence: 99%
“…In addition to facilitating the control of the greenhouse microstructure, Recurrent LSTM Neural Network (R-LSTM-NN) and Deep Belief Network (DBN) (Batov, 2015;Raza and Khosravi, 2015;Lokshina et al, 2019;Zhang K. et al, 2021) have been proven useful in real-life fire hazard prevention and hazard warning (Bu and Gharajeh, 2019). genetic algorithm (GA), and adaptive neuro-fuzzy-inferencesystem (ANFIS), and artificial neural network (ANN), have been proven useful in similar applications (Arabasadi et al, 2013;Naser, 2019;Ronchi et al, 2019) and ecological monitoring (Molinara et al, 2021) using vision-based sensors (Bu and Gharajeh, 2019). The real-life applications would be augmented by robust R&D.…”
Section: Potential Solutions: Polymer Electrolyte Membrane Fuel Cell Stacks Double Skin Facades and Annsmentioning
confidence: 99%
“…Regarding the field of human behavior in fire, Kuligowski [5] gathered all the available data, studies and research at that moment, including evacuation dynamics, timing for certain aspects of building evacuations, analysis of the characteristic movements of vulnerable population, and modelling of evacuation movements. More recently, Ronchi et al [6] summarized recent findings in the field of fire evacuation modelling of different topics within research disciplines outside fire safety engineering, including Applied Mathematics, and Dynamic Simulation and Biomechanics, aiming to study the feasibility of development and application of modelling methods based on these fields and to discuss their implementation strengths and limitations.…”
Section: Related Workmentioning
confidence: 99%
“…Li et al [8] designed a fire evacuation model based on the dynamic coupling of the Fire Dynamics Simulator (FDS) and cellular automata (CA), then analyzed crowd behavior during evacuation using computer simulation based on multi-agent technology. Ronchi et al [9] presented that the evacuation areas should be reasonably divided into workshops, while external staircases and safety exits should be added to the upper floors of the workshop. In addition, safety management should be strengthened through the analysis of evacuations in a workshop.…”
Section: Introductionmentioning
confidence: 99%