Overcoming data shortages through hybrid machine learning in air quality forecasting: a case study of Kağıthane, Istanbul
A hybrid machine-learning framework for AQI prediction in Kağıthane, Istanbul, Türkiye, using a long-term dataset spanning approximately ten years, thereby reducing reliance on dense sensor infrastructures and achieving overall accuracy of approximately 98%, enabling timely health advisories and more efficient allocati...