Research on Urban Street Order Based on Data Mining Technology

Abstract

With the promotion of urbanization, more and more people enjoy the happiness brought about by the urban development, but the type of problems and the amount of problems in urban management are increasing. Under the background of new era, the direction and requirement of the city governance has promoted influenced by the “Internet Plus” strategy and big data strategy. In the construction of information and intelligent construction of urban management, a large number of city operation and management data have been emerged and accumulated, which provide favorable basic conditions for urban research. Through literature reading and field research, this paper made an in-depth study of the current situation of urban management in a city of Zhejiang province. In view of the actual demand of a city in the street order, this paper takes the data fusion cleaning of the street sequence data combined with data mining technology. It builds a Street classification and prediction model by using the decision tree C5.0 algorithm, and a high incidence area classification prediction model by using the Apriori algorithm. The information and knowledge of street order are analyzed. On this basis, this paper designs a street order decision support system, and uses web technology and visualization technology to realize the function modules of street order data service, analysis application, scene display and decision support. The research content of this paper is oriented to the actual demand in the city’s street sequencing work, which provides a favorable support for the actual business of urban management, and also provides decision support for urban management.