Optimizing rural household waste management in Anhui Province using system dynamics and AI-based modeling

Abstract

This study evaluates the effects of policy regulations on rural household waste management in Anhui Province and explores strategies to optimize waste reduction and resource recovery. A system dynamics model was developed to simulate three regulatory scenarios: environmental, economic, and technological. Results indicate that environmental regulation most effectively reduces waste generation, closely approaching the system’s optimization goal, while economic and technological measures show smaller impacts. To enhance predictive accuracy, the Random Forest Algorithm–Sparrow Search Algorithm (RFA-SSA) algorithm was applied, achieving a nonlinear fitting degree of 0.99. Mean Impact Value (MIV) analysis further reveals that rural development factors exert the strongest influence on annual recovery of waste and recyclable resources, whereas construction investment intensity most significantly affects the total annual amount of waste treated in an environmentally friendly manner. These findings provide both qualitative and quantitative evidence supporting public participation in rural waste resource utilization and offer a theoretical foundation for promoting sustainable and stable rural waste management practices.