Exploration Of Planning And Layout Of Elderly Care Facilities Based On Spatial Big Data Mining

In the context of increasing ageing,the miniaturization and declining birthrate of the family structure has made more and more elderly people tend to use the old-age care institutions to solve the problem of old-age care.The aging of Wuhan has been developing year by year,and the large and high proportion of the elderly population has made the supply of elderly care institutions in short supply.According to the pension plan,Wuhan currently implements the "9046" pension model(that is,90% of the elderly are at home,4% of the elderly are in the community,and 6% are in social institutions.)Elderly care institutions will play an important role in assisting home care,providing community care services and institutional care services.The current number of elderly care facilities in Wuhan still has problems such as insufficient number and irrational spatial planning.The importance of planning the location of care facilities in urban space is very important,and the global optimal quantitative location decision-making method needs urgent research.In this paper,Wuhan City is used as the research scope.Based on the500-meter-by-500-meter grid fine-scale,based on the heterogeneous data of massive POI spatial data and the sixth national census data,combined with the existing spatial distribution of nursing facilities Characteristics,using the machine learning algorithm based on ID3 algorithm and GIS(Geographic Information System)to simulate the location of suitable nursing facilities in Wuhan.Finally,4878 suitable elderly care facilities were selected from 31,390 grid areas in Wuhan.Then combining the aging degree of 184 streets with the spatial distribution of the number of elderly population,the 1366 points that need more priority in planning and layout were screened out,and the quantitative location decision of urban aged care facilities on a fine scale was initially realized.It can be said that the government’s later decision-making provides support With reference.The conclusions of the study are as follows:(1)The prediction result is compared with the existing nursing facilities by sampling and testing,and the final accuracy reaches 95.7%,and the spatial distribution of the results is compared with the space of Wuhan nursing facilities announced by Wuhan Natural Resources Bureau Comparison of the layout planning(2012-2020)found that the two are more consistent,indicating that the prediction method is more reliable;(2)The suitable location of the nursing facility location based on the machine learning algorithm will achieve the global optimal level of the entire city of Wuhan Compared with the general manual site selection decision,it will be more objective and scientific;(3)The distribution of elderly facilities and the distribution of the elderly population show a correlation,so new elderly facilities should pay attention to the core within Wuhan’s current second-ring ring where the elderly population is highly concentrated In urban areas,the planning and layout of old-age care facilities in some deeply aging streets in the far urban areas such as Xinzhou District,Huangpi District and Caidian District should be guaranteed.