Visual Analysis Of The Characteristics Of Domestic Floating Population Based On Clustering Algorithm

With the rapid development of modern communication technology and transportation facilities,the data generated by transportation users presents an explosive growth.The exchange of personnel between cities and regions produced a series of flow data,through the comparative analysis of large data of the floating population,especially the geographical position,residence will analysis,data characteristics,can more clearly see that the general direction of the population flow.Visual analysis of the characteristics of domestic population flow can be used to study the relationship between urban systems,as well as to identify urban agglomerations.One of the significant topics in current urbanology is to find out the prominent areas and potential directions of urban development.Combining the clustering algorithm of datamining technology to study the spatial distribution,composition and changing trend of urban population,we can see which areas have more development potential,which cities are growing and which cities are shrinking.It is of great reference to urban development and resource allocation.Some significant work is presented in this thesis:1.A method for visual analyzing the characteristics of floating population data based on clustering algorithm is proposed in this thesis.The main process of this method is as follows: firstly,the initial data set is obtained by processing the dynamic monitoring survey data of the floating population applied by the National Health Floating population Data platform,and then it is divided according to the regional level,geographical location segmentation,and the establishment of a custom location dictionary.Secondly,relevant visualization methods and technical framework are used to dynamically display the data.For the data of any region in China,the clustering algorithm is used to infer the agglomeration effect of the city,and the relationship between regions is found by combining the gravity model.2.Combined with the method proposed in this thesis,a floating population data feature analysis visualization system is implemented.The system consists of three parts:the distribution of inflow population,urban agglomeration effect and regional connection analysis.The integration of various modules and the interaction of data between the diagrams and modules to meet the needs of users in various regions of the study.The visualization system in this thesis provides a new analysis method for visualization application in the research of floating population data,and evaluates the feasibility of the system by analyzing real cases.