A grey-forecasting based multiple linear regression model for planning nursing homes

School of Transportation Engineering, Nanjing Tech University, Nanjing, Jiangsu, China

^* Corresponding author: Guanghua.ren@gecacademy.cn

Abstract

With the increasing demand for elderly care institutions in society, the issue of elderly care has become a serious social problem and a widely publicised livelihood issue. In order to actively respond to the trend of a deeply ageing population, the infrastructure of urban elderly care services is being strengthened. Led by relevant government departments, many scholars are exploring a model suitable for the development of elderly care in China, taking into account the experience of elderly care services at home and abroad. This paper proposes a universal planning model for elderly institutions based on multivariate integer linearity, introducing the zoning method and grey forecasting. It solves the problem of deciding the number of elderly institutions to be built in each district of a particular city in the government's future planning. Using Nanjing as an example, the model is then substituted with data from the Nanjing Rating Standards for Nursing Homes (for Trial Implementation) to obtain a table of construction plans for various types of nursing homes in five major stages during the period 2021-2035 and a map of the recommended distribution of nursing homes. The model simplifies complex calculations by transforming multivariate non-linear problems into linear ones. The simulation results have been proved to be practical and universal. The research results of the thesis can provide a theoretical basis and decision-making reference for the construction projects of elderly institutions and other functional infrastructures where the population gathers, which is conducive to the promotion of urbanisation and pulling economic growth, and provides material guarantee for the improvement of people's living standards..