Prediction and Operation Design of Elderly Care Market Based on Multiple Linear Regression and Regional Clustering

For the elderly care market, a prediction model for the number of nursing beds is established based on multiple linear regression and grey prediction, a regional evaluation model for the elderly care market is established based on TOPSIS and entropy weight method, and a clustered operation model for the elderly care market is established based on Euclidean distance algorithm and hierarchical clustering. The model was validated using medical, population and macroeconomic data of China in recent ten years and various provinces. The results show that the elderly care market will keep growing in the next five years, and the situation of the elderly care market varies greatly among different regions. Then, from the perspective of the government and enterprises, it puts forward suggestions on the operation of the elderly care industry.