Support Vector Machine Regression Optimised by Genetic Algorithms for Calculating the Ageing Population

The aging problem has an increasing impact on China's economy, employment, and medical care, so it is important to make accurate predictions of the aging population. In this paper, we use genetic algorithm (GA) to optimize the initial parameters of support vector regression (SVR) model, and use the optimized SVR model to predict China's aging population using the population data in the 2023 National Statistical Yearbook released by the National Bureau of Statistics (NBS) as a data example. The experiment proves that under the guiding principle of constructing a prediction system that is close to the actual target throughout, the SVR model after parameter optimization using genetic algorithm has good prediction accuracy, scientifically predicts the trend of population ageing, and is conducive to the realization of a practicable multilevel old-age security system.