Fire safety evaluation capability construction method based on big data

Abstract

A fire safety evaluation capability construction method based on big data comprises the following steps: S1, acquiring related historical business data of a fire business unit and a fire duty unit, and counting historical fire reasons in a region by taking a month as a unit to obtain a fire event sample; s2, preliminarily selecting a fire index from the fire event sample; s3,dividing the fire indexes into boxes; s4, screening low-prevention and low-measurement capability indexes; s5, setting an index scoring rule; s6, setting an index weight; s7, establishing a fire safety evaluation model andverifying the model; outputting the model after successful verification. According to the invention, a large amount of fire data is divided into boxes and fire-related factors are screened; the weight of each related factor is determined, and the calculation model of the fire safety evaluation score is constructed, so that the fire safety evaluation capability can be provided for the fire safetywork of cities, the risk of fire in urban areas can be evaluated, and the fire hidden danger troubleshooting work can be guided.

Description

technical field [0001] The invention relates to the technical field of urban public safety, in particular to a method for building fire safety evaluation capabilities based on big data. Background technique [0002] Fire protection work is an important part of national economic and social development, and an important guarantee for building a harmonious society. The identification and elimination of fire hazards is an important topic of urban fire safety, and it is also an important part of the "four capabilities" proposed by the Ministry of Public Security to build a social fire safety "firewall" project. [0003] The comprehensive evaluation of fire safety risk refers to analyzing the set of factors that affect regional fire safety based on statistics, such as the nature of buildings, age, and the accumulation of sundries; The method of system engineering examines the interaction of various system elements, and evaluates the fire safety performance of the entire evaluatio...

AI Technical Summary

Problems solved by technology

At present, the selection of sub-item indicators and the setting of the weight of sub-item indicators are relatively subjective, easily affected by the experience and level of business personnel, and lack of objectivity; the large amount of data generated in the current smart city construction has not been reasonably applied, and there is a lack of a usable Standardized evaluation criteria for horizontal comparison

Especially in the face of complex fire-related factors, how to filter and extract the most suitable index items for evaluating fire risk and set specific weights, there is still no mature and reliable method

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