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Urban accident disaster evolution simulation and risk prediction early warning method

A technology for risk prediction and accidents, applied in the field of machine learning, to solve problems such as inability to work

Active Publication Date: 2020-10-20
CHINA UNIV OF MINING & TECH (BEIJING) +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The downside of this approach is that it has to rely on a lot of collected data and cannot work without enough data

Method used

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  • Urban accident disaster evolution simulation and risk prediction early warning method
  • Urban accident disaster evolution simulation and risk prediction early warning method

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Embodiment 1

[0017] The present invention utilizes machine learning technology and method to realize the parameter training and parameter learning of the urban accident disaster machine learning fast prediction model by using various data to construct the urban accident disaster evolution data warehouse. The machine learning fast prediction model will pass the video monitoring data, The analysis and calculation of real-time monitoring data of sensors can realize the rapid prediction and early warning of urban accident and disaster risks. Among them, the urban accident disaster evolution data warehouse includes various types of data as follows:

[0018] 1. Real-time monitoring data of various sensors in the city;

[0019] 2. Historical data of various accidents and disasters;

[0020] 3. Experimental data of various urban accidents and disasters;

[0021] 4. High-confidence numerical simulation data of various urban accidents and disasters.

[0022] The data warehouse established in the ...

Embodiment 2

[0026] figure 2 It is a structural block diagram of an embodiment of the present invention, which realizes the disaster evolution simulation and risk prediction and early warning of gas leakage accidents in urban underground utility tunnels. Based on the existing experimental data of gas leakage in the comprehensive pipeline gallery and the numerical simulation data of gas leakage in the comprehensive pipeline gallery with high confidence, a data warehouse of gas leakage accidents in the cabin of the comprehensive pipeline gallery can be established. Among them, the numerical simulation data of gas leakage in the comprehensive pipeline gallery with high confidence is generated through two types of models: 1. The numerical simulation model of gas leakage and diffusion in the comprehensive pipeline gallery verified by experimental data or historical data of accidents and disasters; Gas leakage source estimation and diffusion prediction correction model for pipe gallery. Based ...

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Abstract

The invention discloses an urban accident disaster evolution simulation and risk prediction early warning method, and belongs to the technical field of machine learning. An urban accident disaster data warehouse integrating multiple types of data is established, and a machine learning technology is utilized to construct an urban accident disaster evolution simulation and risk prediction early warning machine learning prediction model, so that rapid and accurate prediction of accident disaster evolution and rapid prediction early warning of accident disaster risks are realized. The data warehouse integrates urban accident disaster historical data, urban accident disaster experimental data, real-time monitoring data of various sensors and high-confidence urban accident disaster evolution numerical simulation data. The high-confidence urban accident disaster evolution numerical simulation data is generated by a numerical simulation model verified by accident disaster historical data or experimental data, or is generated by a numerical simulation model based on data assimilation technology fusion numerical simulation model and accident historical data or experimental data, so the problem of insufficient data volume of a data warehouse is solved.

Description

technical field [0001] The invention specifically relates to a method for urban accident disaster evolution simulation and risk prediction and early warning, and belongs to the technical field of machine learning. Background technique [0002] In recent years, with the rapid development of my country's economy and society, the level of urbanization has been continuously improved. However, due to the acceleration of urbanization and the deterioration of the natural environment, the rapid increase of disaster-causing factors and the frequent occurrence of urban accidents and disasters in our cities have led to a very severe form of urban public security in our country. At present, there are various types of urban accident disasters, which have the characteristics of diversity, coupling and chaining. At the same time, due to the characteristics of urban population concentration and dense buildings, if urban accidents and disasters cannot be predicted, early warning and emergen...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06Q10/06G06Q50/26G06F16/27G06F16/28G06N7/00G06N20/00G06F111/10
CPCG06F30/27G06Q10/0635G06Q50/26G06F16/27G06F16/283G06N20/00G06F2111/10G06N7/01
Inventor 吴建松胡啸峰原帅琪沈兵蔡继涛
Owner CHINA UNIV OF MINING & TECH (BEIJING)