Elderly Care Resources and Aging Cognition of New-type Elderly and Traditional Elderly: Evidence from China Using Support Vector Machine

New-aged elderly people prefer various cultural elderly care methods. They enjoy traveling and attending senior universities. Traditional elderly people focus more on taking care of descendants. They also handle household chores. This study examines the differences in cultural elderly care choices. It explores how the mentalities of new and traditional elderly people affect these choices. The study provides references for elderly care resource allocation. The study uses survey data from 1,583 elderly individuals in Dezhou City. It analyzes several factors. These include age, marital status, education, economic background, and community embedding. It examines how these factors influence cultural care preferences. A Support Vector Machine (SVM) model helps identify patterns in these preferences. It also detects key influencing factors. Additionally, the study explores how machine learning can optimize elderly care resource allocation. Cultural elderly care preferences are closely related to these factors. Younger elderly individuals prefer diverse cultural elderly care activities. They often have a spouse or partner. Basically, they are educated and hold better economic conditions. Several younger individuals use the Internet services. Traditional older people are more impacted by their obligations. They elevate grandchildren and take care of family responsibilities. The research outcomes recommends that social ageing care requirements should be part of public policy development. Services need to fit the unique needs of various elderly groups. Using machine learning methods like SVM can offer valuable information for personalized care. They can also help with better distribution of care resources.