Traffic risk prediction method based on complex network theory

Abstract

The invention provides a traffic risk prediction method based on a complex network theory. The traffic risk prediction method comprises the following steps: step A, dividing grids based on empirical data to construct a double-layer traffic network model; step B, carrying out feature extraction and screening based on a complex network theory; c, performing risk prediction based on an ensemble learning theory; d, evaluating and verifying the model; through the above steps, two dimensions of functions and structures of the traffic system are comprehensively considered, scientific and reliable technical support and theoretical support are provided for identification of traffic risks, and important support is provided for risk diagnosis of the traffic system, formulation of targeted managementcontrol measures and improvement of traffic operation reliability. The method is high in systematicness, high in portability and easy to operate, and the problem that risks in a complex traffic systemare difficult to identify and predict is solved.

Description

technical field [0001] The invention proposes a traffic risk prediction method based on complex network theory, which relates to technical fields such as risk analysis and network science. Background technique [0002] Risk refers to an event that may occur. If it occurs, it can hinder the development of the system, or even decline. Risk is also defined as the uncertainty of whether the event occurs or not. Risks exist objectively in the system, and the losses caused by risks can be prevented or reduced by adopting preventive measures, but the risks cannot be eliminated. In a complex system, the risks in the system often appear in the characteristics of sudden occurrence, wide spread, and strong destructive power, which brings great difficulties to the identification, prediction and prevention of system risks, and also poses a challenge to the risk management control and prevention of complex systems. Research poses new challenges, and the losses caused by the occurrence of...

AI Technical Summary

Problems solved by technology

[0005] The present invention is mainly used to solve the problem of risk identification and prediction under the background of complex systems and network structures. At present, the existing methods mainly analyze the risks of the traffic system from the perspective of system functions, aiming at the high complexity of the traffic system and its spatial and temporal evolution characteristics, current Some methods cannot identify and predict system risks well. Therefore, aiming at the deficiencies of existing methods, this invention starts from the perspective of complex networks and comprehensively considers the two dimensions of traffic system functions and structures, and proposes a method based on complex networks. Theoretical Traffic Risk Prediction Method

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