Rule-Based Grass Biomass Classification for Roadside Fire Risk Assessment

2016 ◽  
pp. 636-644
Author(s):  
Ligang Zhang ◽  
Brijesh Verma
Keyword(s):  
Risk Assessment ◽  
Fire Risk ◽  
Rule Based ◽  
Fire Risk Assessment ◽  
Grass Biomass

Fire Risk Assessment of Composite Materials in Aviation by Hazard Levels Characterized in Standard EN 45545

2020 ◽  
Vol 13 (5) ◽  
pp. 182
Author(s):  
Stanislav Szabo ◽  
Iveta Vajdova ◽  
Edina Jencova ◽  
Daniel Blasko ◽  
Robert Rozenberg ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Composite Materials ◽  
Fire Risk ◽  
Fire Risk Assessment ◽  
Hazard Levels

Research on Fire Risk Assessment for Factory-Type Buildings

2008 ◽  
Vol 18 (1) ◽  
pp. 61-77
Author(s):  
Jen-Hao Chi ◽  
Cheng-Tung Chen ◽  
Jia-Woei Chen
Keyword(s):  
Risk Assessment ◽  
Fire Risk ◽  
Fire Risk Assessment

scholarly journals Fire risk assessment, spatiotemporal clustering and hotspot analysis in the Luki biosphere reserve region, Western DR Congo

2021 ◽  
pp. 100104
Author(s):  
Nadège CIREZI CIZUNGU ◽  
Elvis TSHIBASU ◽  
Eric LUTETE ◽  
Arsene MUSHAGALUSA ◽  
Yannick MUGUMAARHAHAMA ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Biosphere Reserve ◽  
Fire Risk ◽  
Dr Congo ◽  
Hotspot Analysis ◽  
Fire Risk Assessment ◽  
Spatiotemporal Clustering

scholarly journals Fire Risk Assessment in Healthcare Settings: Application of FMEA Combined with Multi‐Criteria Decision Making Methods

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Fateme Omidvari ◽  
Mehdi Jahangiri ◽  
Reza Mehryar ◽  
Moslem Alimohammadlou ◽  
Mojtaba Kamalinia
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Fire Risk ◽  
Fire Detection ◽  
Healthcare Setting ◽  
Multi Criteria Decision Making ◽  
Intuitionistic Fuzzy ◽  
Healthcare Settings ◽  
Fire Risk Assessment ◽  
Risk Parameters

Fire is one of the most dangerous phenomena causing major casualties and financial losses in hospitals and healthcare settings. In order to prevent and control the fire sources, first risk assessment should be conducted. Failure Mode and Effect Analysis (FMEA) is one of the techniques widely used for risk assessment. However, Risk Priority Number (RPN) in this technique does not take into account the weight of the risk parameters. In addition, indirect relationships between risk parameters and expert opinions are not considered in decision making in this method. The aim is to conduct fire risk assessment of healthcare setting using the application of FMEA combined with Multi‐Criteria Decision Making (MCDM) methods. First, a review of previous studies on fire risk assessment was conducted and existing rules were identified. Then, the factors influencing fire risk were classified according to FMEA criteria. In the next step, weights of fire risk criteria and subcriteria were determined using Intuitionistic Fuzzy Multiplicative Best-Worst Method (IFMBWM) and different wards of the hospital were ranked using Interval-Valued Intuitionistic Fuzzy Combinative Distance-based Assessment (IVIFCODAS) method. Finally, a case study was performed in one of the hospitals of Shiraz University of Medical Sciences. In this study, fire alarm system (0.4995), electrical equipment and installations (0.277), and flammable materials (0.1065) had the highest weight, respectively. The hospital powerhouse also had the highest fire risk, due to the lack of fire extinguishers, alarms and fire detection, facilities located in the basement floor, boilers and explosive sensitivity, insufficient access, and housekeeping. The use of MCDM methods in combination with the FMEA method assesses the risk of fire in hospitals and health centers with great accuracy.

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