| By systematically analyzing the temporal and spatial factors of traffic accident distribution,this paper makes a preliminary exploration on the causes of accidents and traffic accident early warning methods.On this basis,this paper summarizes the theoretical methods of traffic accident early warning system,and analyzes and studies the traffic accident early warning methods based on data mining.Firstly,the research status and safe road traffic management measures at home and abroad are systematically summarized by consulting the current literature and description of traffic accidents at home and abroad.On this basis,this paper systematically analyzes the spatio-temporal data of urban road safety and the relevant laws revealed in the research process in this field,and then improves the Apriori algorithm by mapping and storing the target transaction database.Combined with the improved Apriori algorithm and the improved FP Tree algorithm,this paper puts forward the mifp Apriori algorithm,Based on this algorithm,the correlation between the detailed factors affecting road traffic safety mentioned in the above process is systematically analyzed.Through the specific content association analysis of the high-frequency project group generated by the association rules,the potential relationship is constructed by data mining and matching analysis.Then,this paper uses Bayesian network to analyze and construct the causes of traffic accidents and risk prediction,systematically learns the model structure and model parameters of Bayesian network by using netica software and K2 algorithm,and completes the construction process of traffic accident prediction model.Using this model,data set analysis and accident cause analysis are carried out,and the early warning probability of regional accidents is calculated,So as to achieve the effect of quantitative and qualitative analysis of road traffic safety.According to the prediction results and the application of traffic accident early warning model,carry out safety early warning of traffic accidents.Finally,based on the SSM development framework,combined with the improved association rule algorithm and Bayesian network model,a traffic accident early warning platform is developed,and the traffic accident early warning function is developed.Starting with the analysis of association rules and Bayesian network classification,this paper studies the data samples to carry out the accident early warning based on influencing factors,which provides auxiliary guidance and help for traffic management to a certain extent.With this technology,the traffic management department can formulate corresponding traffic safety prevention measures and regulations,and reduce the probability of accidents through certain countermeasures,so as to reduce the losses caused by accidents. |
