Analysis and Forecasting Research on Supply and Demand Relationship of Smart Elderly Care Based on Random Forest and ARIMA Models

Abstract

With the aging of the population, the demand for elderly care services is increasing, and the contradiction between supply and demand is becoming more and more prominent. Under the background of big data and artificial intelligence, intelligent aging has become a trend for future development. Taking the six urban areas in the centre of Tianjin as an example, this paper explores the influencing factors and future development trend of intelligent aging development, and explores effective countermeasures to cope with the aging problem. This paper adopts the relevant data of the whole country and Tianjin from 2015 to 2023, constructs the indicator system affecting the development of smart old-age care, and analyses the influencing factors by using the entropy value method evaluation model. It is found that the main factors restricting the development of smart old-age care focus on the two aspects of residents' life and old-age care services, especially the number of nursing home beds and per capita disposable income of residents. Based on this, this paper establishes a supply relationship model based on the Lorenz curve and the Gini coefficient to analyse the supply and demand relationship of senior care facilities in Tianjin, revealing problems such as the oversupply of facilities, unbalanced distribution, and insufficient matching demand for different levels of senior care institutions. Further, this paper identifies the key factors affecting the changes in the number of nursing home beds through the random forest method, and constructs an ARIMA prediction model to predict the future demand for beds in six urban areas of Tianjin to alleviate the contradiction between supply and demand. The model construction in this study provides theoretical support for promoting the development of intelligent elderly care.