Research on Relationship Between Aging Population Distribution and Real Estate Market Dynamics based on Neural Networks
Yiqiu Tang, Shenghan Zhao · Preprints.org · 2025
The present study explores the relationship between demographic shifts and fluctuations in the real estate market. Utilizing a neural network approach, this study investigates the relationship between the distribution of an ageing population and the dynamics of the real estate market. The proposed model utilizes a deep learning framework, incorporating a single long short- term memory network (LSTM) with multiple optimization techniques, adaptive learning rates, and data augmentation strategies. This integrated approach is designed to effectively capture the intricate interplay of factors such as population age structure, migration patterns, and economic indicators on real estate market dynamics. The model's efficacy is demonstrated by its capacity to predict market trends with a high degree of accuracy, in addition to its ability to effectively respond to the impact of the aging population on housing prices in various geographical regions. Experimental findings demonstrate that the proposed LSTM model surpasses conventional statistical methodologies in terms of prediction accuracy. Furthermore, it exhibits notable generalization capabilities and robustness across diverse market contexts.