Interpretable PM2.5 Forecasting for Urban Air Quality: A Comparative Study of Adaptive Time-Series Models
These findings show that lightweight additive forecasting strategies can remain highly competitive for urban air-quality prediction, offering a practical balance between accuracy, interpretability, and computational efficiency.
Moazzam Umer Gondal, Hamad Ul Qudous, Asma Ahmad Farhan et al.
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