Research On Urban Affordable Housing Site Selection Based On BP Neural Network

For a long time,housing has been a spiritual sustenance of the residents of our country for "hometown feelings",and it is also the basis for the people to settle down.China's housing policy has continued to improve and develop from national security to market supply and then to social security.During this period,affordable housing has developed vigorously,but it is also facing various difficulties.On the one hand,the remote and concentrated distribution of affordable housing has exacerbated the differentiation of living space.The rich and the poor have gradually begun to solidify and label,and the resource distribution has been unfair.The construction of suburban affordable housing has increased the pressure on traffic and public service facilities.The irreversible nature of the building has also caused a lot of high-quality land to be wasted by unreasonable planning and layout,causing serious economic and environmental problems.In this context,it is necessary to optimize the early site selection of affordable housing,so that a reasonable layout method can effectively improve the utilization efficiency of land resources,improve the happiness of residents,and avoid the development of social housing falling into vicious development.This article takes the optimization of affordable housing site selection as a starting point,and through interviews and literature surveys,considers the influencing factors of affordable housing site selection from five aspects of transportation,basic supporting facilities,living environment,employment conditions,land costs,etc.Influencing factors,on this basis,use BP neural network to establish a site selection evaluation model,judge the merits of site selection,analyze the reasons and get an optimization plan.Finally,taking Fuzhou's public rental housing as an example,according to the current situation of Fuzhou's public rental housing site selection layout,the built BP neural network location model is used,and the operation is performed through MATLAB software to determine the advantages and disadvantages of the location selection plan,and the The site selection plan proposed an optimization strategy.In turn,the overall site selection plan is improved,the rationality of site selection is improved,and the objectivity and operability of the optimization of site selection for affordable housing is enhanced.The results of this study have four aspects: one is the importance of optimizing the location of affordable housing;the second is to summarize and analyze the characteristics,disadvantages and causes of the location of affordable housing in China at the present stage;the third is to obtain affordable housing based on the survey Influencing factors of site selection layout.The fourth is to establish an operable and practical model based on BP neural network,and take the affordable housing in Fuzhou as an example to evaluate and optimize the location plan of affordable housing.