Supercharge Your Innovation With Domain-Expert AI Agents!

Multiple linear regression fire risk assessment method based on big data

A multiple linear regression and risk assessment technology, applied in data processing applications, instruments, resources, etc., can solve difficult problems such as smart fire protection applications

Inactive Publication Date: 2018-12-21
SHENYANG FIRE RES INST OF MEM
View PDF5 Cites 13 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although the evaluation results are relatively accurate, it is difficult to use them conveniently and quickly in the smart fire protection system

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Multiple linear regression fire risk assessment method based on big data
  • Multiple linear regression fire risk assessment method based on big data
  • Multiple linear regression fire risk assessment method based on big data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0060] The present invention provides a multiple linear regression fire risk assessment method based on big data, which uses a multi-attribute assessment method, the model is widely used in complex systems due to its convenience and robustness, and the heuristic process of associating these attributes constructs a Robust fire risk assessment system. This multi-factor comprehensive risk assessment method determines the main factors affecting the risk, solves the data standardization problem of each factor, and completes the establishment of the risk assessment model.

[0061] (1) Construct a hierarchical structure model of fire risk factors

[0062] In the multi-factor comprehensive risk analysis, the selection and determination of factors are very important. The factors affecting the fire safety of social units in the field of fire protection include five aspects: (1) fire hazard source; (2) building fire protection; (3) personnel situation; ( 4) Fire safety management of soc...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to a multivariate linear regression fire risk assessment method based on big data, which is used in the field of data processing and analysis. Comprises the following steps of: (1) constructing a hierarchical structure model of fire risk factors; (2) dividing a building fire risk grade; (3) Establish the evaluation model R=WTX; (4) Constructing the data sample of risk assessment machine learning; 5, calculate that weight W according to the sample, and establish a fire safety fire risk assessment model R=WTX; (6) Calculating the attribute value of the building to be evaluated according to the step (4.1), and comparing the risk value calculated by the model established in the step (5) with the risk grade divided in the step (2) to obtain the risk grade of the building.This method adopts multi-attribute evaluation method, realizes the quantitative evaluation of fire risk grade, and comprehensively evaluates the fire safety management risk of social units.

Description

technical field [0001] The invention relates to a fire risk assessment method based on big data and machine learning, belonging to the field of data processing and analysis. Background technique [0002] With the rapid development of today's society, fire has already become a disaster that cannot be ignored. How to actively detect and warn in advance, and how to reduce the fire risk in social units has always been the basis of socialized fire protection work. With the development of science and technology, fire risk assessment methods based on big data, cloud computing, and artificial intelligence continue to mature. Through the analysis and mining of massive historical data, a scientific fire risk assessment system has been established. Through the fire risk assessment of social units, determine their fire safety levels, discover risk items, guide them to improve fire safety mechanisms, and improve fire safety levels, thereby reducing risks, protecting people's lives and pr...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06Q10/06G06Q50/26
CPCG06Q10/0635G06Q50/265
Inventor 邢翱徐放隋虎林刘濛王军
Owner SHENYANG FIRE RES INST OF MEM
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com