City Fire Risk Assessment Model Based on the Adaptive Genetic Algorithm and BP Network

2012 ◽  
Author(s):  
Jiao Aihong ◽  
Yuan Lizhe
Keyword(s):  
Genetic Algorithm ◽  
Risk Assessment ◽  
Fire Risk ◽  
Assessment Model ◽  
Adaptive Genetic Algorithm ◽  
Risk Assessment Model ◽  
Bp Network ◽  
Model Based ◽  
Fire Risk Assessment

scholarly journals Developing a Subway Fire Risk Assessment Model Based on Analysis Theory

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Zhenguo Yan ◽  
Yanping Wang
Keyword(s):  
Risk Assessment ◽  
Evaluation Method ◽  
Fire Risk ◽  
Control Measures ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Model Based ◽  
Analysis Theory ◽  
Fire Risk Assessment ◽  
And Control

In order to effectively reduce the risk of subway fires and to improve the safety of passengers, a review of the background to subway fires employing literature and comparative analyses, computer simulation, expert consultation, and other research methods has been employed to conduct an in-depth study of subway fire risk assessment and control measures. A subway fire risk assessment model based on analysis theory was established. Firstly, a subway fire risk evaluation index system was developed, and the weight values of each level were determined using the interval analytic hierarchy process (IAHP), then the evaluation was derived using the fuzzy evaluation method, and the passenger distribution simulation was introduced to improve the objectivity of the evaluation. The results show that the fire evaluation of this subway system is safe. The results show that a subway fire risk assessment model may provide a scientific basis for establishing prevention and control measures, extinguishing methods, passenger safety evacuation schemes, and carrying out fire safety management activities during subway operations.

scholarly journals A fire risk assessment model for residential high-rises with a single stairwell

2018 ◽  
Vol 95 ◽  
pp. 160-169 ◽  
Author(s):  
N.D. Hansen ◽  
F.B. Steffensen ◽  
M. Valkvist ◽  
G. Jomaas ◽  
R. Van Coile
Keyword(s):  
Risk Assessment ◽  
Fire Risk ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Fire Risk Assessment

scholarly journals Spatiotemporal Analysis of Active Fires in the Arctic Region during 2001–2019 and a Fire Risk Assessment Model

Fire ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 57
Author(s):  
Zhen Zhang ◽  
Leilei Wang ◽  
Naiting Xue ◽  
Zhiheng Du
Keyword(s):  
Risk Assessment ◽  
Logistic Regression ◽  
Vegetation Type ◽  
Fire Risk ◽  
Fire Frequency ◽  
Assessment Model ◽  
The Arctic ◽  
Polar Regions ◽  
Risk Assessment Model ◽  
Fire Risk Assessment

The increasing frequency of active fires worldwide has caused significant impacts on terrestrial, aquatic, and atmospheric systems. Polar regions have received little attention due to their sparse populations, but active fires in the Arctic cause carbon losses from peatlands, which affects the global climate system. Therefore, it is necessary to focus on the spatiotemporal variations in active fires in the Arctic and to assess the fire risk. We used MODIS C6 data from 2001 to 2019 and VIIRS V1 data from 2012 to 2019 to analyse the spatiotemporal characteristics of active fires and establish a fire risk assessment model based on logistic regression. The trends in active fire frequency based on MODIS C6 and VIIRS V1 data are consistent. Throughout the Arctic, the fire frequency appears to be fluctuating and overall increasing. Fire occurrence has obvious seasonality, being concentrated in summer (June–August) and highest in July, when lightning is most frequent. The frequency of active fires is related to multiple factors, such as vegetation type, NDVI, elevation, slope, air temperature, precipitation, wind speed, and distances from roads and settlements. A risk assessment model was constructed based on logistic regression and found to be accurate. The results are helpful in understanding the risk of fires in the Arctic under climate change and provide a scientific basis for fire prediction and control and for reducing fire-related carbon emissions.

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