城市功能区发现的k-means聚类算法

he development of the city has formed different functional areas, and it is of great significance to find and reasonably arrange and plan these functional areas for policy making and resource allocation. At present, with the continuous development of artificial intelligence technology, networking technology and cloud computing technology, the use of urban data for urban planning has become a trend. The diversification of urban transport makes it easier for residents to travel, and the travel of the residents produced a large number of individual mobile data for research. This thesis makes use of the individual mobile data and the POI(Point of Interest) data to make a comprehensive study, and the k-means clustering algorithm is applied to identify the different functional area of the city.