Abstract
Building fires are characterized by high uncertainty, so their fire risk assessment is a very challenging task. Many indexes and parameters related to building fires are ambiguous and uncertain; as a result, a flexible and robust method is needed to process quantitative or qualitative data and update existing information when new data are available. This paper presents a novel model to deal with the uncertainty of the residential building fire risk and systematically optimize its performance effectiveness. The model includes fuzzy theory, evidence reasoning theory, and expected utility methods. Fuzzy analysis hierarchy process is applied to analyze the residential building fire risk index system and determine the weights of the risk indexes, while the evidence reasoning operator is used to synthesize them. Three buildings were selected as a case study to illustrate the proposed fire risk model. The results show that the fire risk level of three buildings corresponds to “moderate” or below which is consistent with the previous study. These results also truly reflect the actual situation of fire safety in these residential buildings. The application of this model provides a powerful mathematical framework for cooperative modeling of the fire risk assessment system and allows data to be analyzed step by step in a systematic manner. It is expected that the proposed model could provide managers and researchers with flexible and transparent tools to effectively reduce the fire risk in the system.
Highlights
With the acceleration of industrialization, urbanization, and marketization in China, building construction industry has developed rapidly
According to the statistics provided by the Ministry of Public Security in 2013, a total of 388,821 fires were recorded in China, in which 52% (202,299) of fires occurred in buildings, resulting in 3410 civilian deaths or injuries and 3760 million Chinese yuan (CNY) direct property losses
A belief structure can solve the problems of fuzziness, uncertainty, and imprecision in human decision-making. erefore, this paper presents a model that combines fuzzy linguistic variables and a belief degree to construct a belief structure with the same set of assessment grades [26]. ese sets’ form of each factor could be expressed as follows: Reasonably likely (RL) RL1, RL2, RL3, RL4, RL5 highly unlikely, unlikely slight, likely, reasonably likely, highly likely, RS RS1, RS2, RS3, RS4, RS5 negligible, slight, moderate, serious, catastrophic, (7)
Summary
With the acceleration of industrialization, urbanization, and marketization in China, building construction industry has developed rapidly. TM responding software have emerged, such as FiRECAM (Fire Risk Evaluation and Cost Assessment Model) [4, 5], FIERAsystem (Fire Evaluation and Risk Assessment system) [6], CESARE-RISK (Centre for Environment Safety and Risk Engineering, RISK) [7, 8], and Crisp II (Computation of Risk Indices by Simulation Procedures) [9]. Xin and Huang proposed scenario cluster methods in the process of the fire risk analysis model for residential buildings [2]. Speaking, these methods reveal two main challenges in an uncertain environment associated with the fire risk factors of the system.
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