Method for enhancing traffic hazard personnel accident risk prediction precision

A technology of accident risk and prediction accuracy, which is applied in the directions of prediction, instrumentation, and data processing applications. It can solve problems such as the difficulty of improving model effects and the complexity of integrated learning models, so as to improve accident risk prediction accuracy, fast convergence speed, and ensure accuracy. Effect

Active Publication Date: 2018-09-28
JIANGSU ZHITONG TRANSPORTATION TECH
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Problems solved by technology

However, the complex parameter composition of the integrated learning model brings certain difficulties to the improvement of the model effect.

Method used

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  • Method for enhancing traffic hazard personnel accident risk prediction precision
  • Method for enhancing traffic hazard personnel accident risk prediction precision
  • Method for enhancing traffic hazard personnel accident risk prediction precision

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Embodiment

[0043] A method to improve the accuracy of accident risk prediction for traffic dangerous persons, using an optimized sampling method to obtain traffic violation data and accident data samples, using integrated learning algorithms to train traffic accident risk prediction models for traffic participants, and further optimizing the model through genetic algorithms to improve The accuracy of prediction results, such as figure 1 . The method of the embodiment uses the integrated learning algorithm to mine the safety characteristics of traffic travelers in the traffic violation data, adopts the optimal sampling method in the sampling link of model construction to improve the performance of the initial model, and uses the genetic algorithm to optimize the model parameters to effectively improve the risk of accidents caused by high-risk personnel. Risk Prediction Accuracy. The specific method flow is:

[0044] S1. Based on the original traffic violation data and accident data, con...

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Abstract

The invention provides a method for enhancing traffic hazard personnel accident risk prediction precision. According to the method, traffic violation data and accident data samples are obtained via anoptimized sampling method; an integrated learning algorithm is used for training a traffic participator traffic accident risk prediction model; and a genetic algorithm is used for optimizing the model. According to the method, the integrated learning algorithm is used for mining safety characteristics of passengers from traffic violation data, the initial model performance is improved in the sampling link of the model construction by adoption of the optimized sampling method, and the genetic algorithm is used for optimizing model parameters, so that the high-risk personnel accident risk prediction precision is effectively enhanced.

Description

technical field [0001] The invention relates to a method for improving the accident risk prediction accuracy of traffic dangerous persons. Background technique [0002] Studies have shown that there is a correlation between traffic violations and traffic accidents, and the attributes and behaviors of traffic participants such as drivers and pedestrians retained by traffic violations can provide data support for the analysis of human factors in traffic safety. Data mining can use the classification idea to mine the safety characteristics of traffic offenders according to the personnel attribute variables. [0003] The traditional classification method is to find a classifier that is closest to the actual classification function in a space composed of various possible functions, but in practice, only a weakly supervised model with preference is usually obtained, and the reliability of the model is not good. The ensemble learning algorithm improves the performance of the final...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/26
CPCG06Q10/04G06Q50/26
Inventor 刘林陈凝吕伟韬马党生
Owner JIANGSU ZHITONG TRANSPORTATION TECH
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