Research On Traffic Accident Rules And Forecast In Poyang County Based On Data Mining

With the rapid development of the global economy and the continuous increase in car ownership,the problems caused by transportation have gradually become more promine nt.Road traffic safety is related to the national economy and people’s livelihood,once a traffic accident occurs,it will not only bring property damage,but also endanger people’s lives.Therefore,using scientific and effective methods to analyze traffic accidents and prevent traffic accidents is of great significance for protecting people’s lives and property safety and national economic development.This article first analyzes the traffic accident data of Poyang County from 2017 to 2019,and uses statistical analysis to analyze the laws of the accident in terms of time,space,type and different climate.On this basis,combined with the GIS system,a nuclear density analysis is performed to identify the accident-prone sections in the area.Secondly,the Apriori algorithm was used to analyze the correlation of the factors that cause urban road and suburban road traffic accidents.In order to fundamentally explore the mechanism of traffic accidents and provide a reference for further prevention of accidents.Finally,based on the BNT software package written in Matlab language,the K2 algorithm was used to learn the sample data structure,and the Netica software was used to learn the parameters,and then the urban road and suburban road traffic accident prediction models based on Bayesian network were constructed.The model was used to predict and analyze the cause of traffic accidents in the study area.It was found that three factors,such as giving in accordance with regulations,improper operation,and speeding,had a higher impact on the road traffic accident patterns in urban areas.The most influential factors on the shape of suburban highway traffic accidents are vehicle models,followed by improper driver operation,speeding,and road alig nment.The research results are basically in line with the actual situation,which verifies the scientificity and practicality of the model.The method based on the combination of GIS spatial analysis and mathematical statistics avoids the spatiotemporal separation of accident analysis and can more accurately identify the occurrence of traffic accidents The traffic accident prediction model based on association rules and Bayesian network eliminates the interference of irrelevant factors on the accuracy of the model and improves the accuracy of the model.The model prediction results can provide reference for the traffic management department.