Design And Application Of Highway Anti-evasion Fee System Based On Data Mining

In recent years,China has invested a lot of funds and manpower in road construction,which has made great progress in road traffic construction.China has a vast territory,so there is an urgent need for a mature Expressway network.At present,the toll system is widely used in expressways in China,but in the operation process,some illegal drivers always use various ways to cheat and evade the toll,which is not conducive to the normal development of highway toll recovery work and reduces the highway traffic management.Reasonable level.In addition,with the increasing number of motor vehicles in our country,a lot of high-speed toll stations have to pass a large number of vehicles every day,resulting in a huge amount of data.How to promote the normal development of highway anti-evasion work through the scientific processing of data has become a topic of widespread concern in the industry.Firstly,this paper analyses and summarizes the research status of the anti-evasion fee system at home and abroad,introduces the related concepts of data warehouse and data mining,and emphatically introduces the steps of building data warehouse and the methods of data mining;secondly,it analyses the requirements of the system and introduces the overall system.Needs,the functional requirements of the system are analyzed in detail,and the non-functional requirements of the system are introduced.Secondly,the overall design of the system architecture and functional structure is carried out.The system database is designed in detail from two aspects of data flow and data table structure,detailed design of the system data preprocessing and data warehouse;At last,the specific application of data mining technology in highway anti-evasion fee system is designed and realized in detail.Data mining technology and association rules algorithm are introduced,and the application of two technologies in this system is explored.Based on the empirical analysis,this paper explores how to optimize the linear regression equation so as to make the budget fee amount as close as possible to the actual fee amount and improve the accuracy of the prediction system.In order to realize the storage and management of massive data in high-speed toll stations,this system chooses the SQL Server 2014 database,which has a very powerful data mining function and can basically meet the needs of the system.Through the data mining function of the database,the traffic flow and toll of the high-speed toll station are predicted,and the possible escaping situation is analyzed through the comparison between the two.When analyzing the vehicle toll data,data cube technology(ie OLAP)is used for multidimensional data calculation,in order to achieve comprehensive monitoring of highway traffic conditions.In addition,the system makes statistics and Analysis on vehicle traffic data of expressway toll station by association rule algorithm,summarizes the law of vehicle traffic,thus realizes the prediction system of vehicle traffic volume and vehicle type,and then uses the European distance isolated point to analyze the abnormal traffic situation and excavate the potential cost escaping situation.And through the timely verification of abnormal data to identify illegal vehicles,and improve the highway toll station vehicle evasion prevention management system,to achieve the purpose of improving management level.