Research On Application Of Apriori Improved Algorithm In Traffic Illegal Data Analysis

As the number of motor vehicles in China grows year by year,the pressure on the transportation system is increasing.Regular road traffic violations are inevitable.Illegal behavior often leads to traffic accidents.Therefore,analysis of the causes of traffic accidents becomes one of the key points in the study of transport systems.Traffic violations are the basis of traffic accidents.By analyzing traffic violations and discovering the relationship between various factors that constitute illegal information,it is possible to better prevent the occurrence of traffic violations.At the same time,with the large-scale growth of data in the information age,knowledge discovery has become a hot topic.Data mining is one of the important steps.The database of China's traffic management department has accumulated a large amount of data,how to make these data play a role.Mining technology is essential.By analyzing the demand of traffic illegal information data,this paper explains the necessity of mining and analyzing the illegal data.Association rules are an important part of data mining,so the association rules mining algorithm can be applied to the analysis of road traffic violation data.Apriori algorithm is a classic association rule mining algorithm,analyzing its basic ideas and implementation steps,discovering that Apriori algorithm generates a large number of candidate itemsets when searching for frequent itemsets,and repeatedly scans the database repeatedly,which causes the algorithm to perform less efficiently.Therefore,in view of the defects in its performance,by removing meaningless data compression data set size and pruning of frequent itemsets to effectively reduce the number of candidate sets,puts forward the improved algorithm--R_Apriori algorithm,improved algorithm is verified by an experiment compared with Apriori algorithm in the superiority of performance.There are many kinds of information in the illegal record table,but they are not all interesting information.Through powerful data mining tools,the data preprocessing process is completed and the processed data is analyzed.Applying R_Apriori to traffic violation data,according to the relationship between different attributes,attribute combinations and illegal activities,analyze traffic violation data and obtain rules that are instructive for practice,so as to better serve traffic management.