Data Mining And Analyze In Freeway Charging System

Data mining is one of the most important information processing technologies. It integrates several mature tools and technologies of other subject and advanced with the development of these subjects. In this paper, a method that combined data mining algorithm and technology to research charging data is designed, and it also provide the basal knowledge for decision-making.The charging system data is a production of system operating. It is an important record which collects operation results. There are many researches on it, and the common one is analysis with statistics theory which brings large workload and low efficiency.Charging system data is inconsistent and including noise, a deficient noisy dataset processing algorithm is designed, which could simultaneously fill the deficient data and clean the noisy data. This paper designed common attribute deficient model generate algorithm and subset generate algorithm which used to seeking frequently losing item and generate subset to fuse the cluster results that solve the problem of integrate algorithm; Common data processing method cannot handling the charging system data properly, data mining algorithm could solve it, conceptual description could provide general characteristic of data and gather the dataset; association analysis is able to find the connection between two dataset; classification and forecasting method is capable to pick up important data model and forecast the trend of data; cluster analysis method is aim to enhance the analyzing ability by classify object data to many different class which is provide with high semblance. Experiments showed that data mining produced more helpful decision-making than common software analysis.