Research On Housing Security Modes Of Rural Migrant Population In The Context Of Big Data

The rural migrant population(RMP)has played a huge role in urban economic construction,providing key labor support for transforming economic development mode,but its housing situation is worrying.Poor housing conditions and imperfect municipal support are the current rural population transfer.A common problem in the environment.The homogeneity of neighbors caused by the housing situation in reality not only hinders the orderly advancement of the rural population transfer process,but also restricts the sustainable development of new urbanization.Therefore,housing security has become a key task in solving the people's livelihood problems in the process of urbanization of rural migrants.Digging out the diversity of housing needs of RMP is the key to improving housing security system.To investigate the above issues,the main work and contributions of the thesis are as follows:Firstly,based on the perspective of housing demand,through the literature analysis,interview interviews and other research methods,from the two dimensions of demography,sociology and current housing conditions,the key characteristics of housing demand for rural migrants are screened.According to the definition of the research object in this paper,the national population dynamic monitoring(CMDS)data is preprocessed by column deletion method.Based on the obtained 2017 survey data,the important attribute indicators affecting the differentiation of housing demand are selected from the characteristics of housing demand characteristics of rural transfer population,and the internal differentiation index system of rural transfer population is constructed.Secondly,aiming at the clustering problem of rural transfer population housing demand,an improved algorithm of hybrid heterogeneous data clustering analysis based on Gower's Distance and contour coefficient is proposed,and a clustering analysis model of rural differentiation population is constructed.This model is used to divide the CMDS 2017 data into multiple dimensions,and comprehensively analyze the demographic,living conditions and housing property demand preference information of each category group,and provide practical support for the formulation of housing security related policies for rural transfer population.Finally,according to the problems and deficiencies in the current housing allocation research and housing security practice,based on the system theory and the housing demand forecast,the traditional housing security model construction process is optimized and improved.On basis of big data technology,the data sharing and decision-making system architecture was proposed.Furthermore,it tried to provide theoretical support and policy recommendations for a sound social security system.