Optimization of Bi-directional Long and Short-term Memory Networks Based on Variational Modal Decomposition Combined with Particle Swarm Algorithm for Health and Longevity Prediction

In this study, an innovative prediction model based on the integration of variational modal decomposition (VMD), particle swarm optimization (PSO) algorithm and bidirectional long and short-term memory network (BiLSTM) is proposed to address the mechanism of economic and social factors on the health life expectancy of the population and prediction problems. The adaptive modal decomposition of complex time-series features by VMD algorithm, combined with the global optimization of key parameters of BiLSTM network by PSO algorithm, effectively solves the limitations of the traditional model in nonlinear data feature extraction and long-term dependency capturing. The empirical results show that the model achieves MAE values of 2.7335 and 2.8195 in the training and test sets, respectively, and the error in the test set is only slightly increased by 0.86 compared with the training set, while the R index in the test set is improved by 0.03 compared with the training set, which shows that the model maintains high prediction accuracy with good generalization ability. The visualization analysis further confirms that the model predictions are highly consistent with the actual healthy life expectancy data in terms of spatial distribution, especially in the fluctuating intervals of the key economic and social indicators, which demonstrates a robust prediction performance. This study not only provides a new quantitative analysis framework for the influence mechanism of healthy life expectancy, but also constructs a prediction model with important application value in the simulation of the effect of public health policies and optimization of health resource allocation, etc. The research results can provide scientific basis for the government to formulate healthy aging policies and promote the development of healthy and equitable development, which is of positive practical guidance significance for the realization of the strategic goal of Healthy China 2030.