Srimuruganandam Bhathmanabhan

A robust and uncertainty-aware machine learning framework for PM2.5 prediction in a coastal urban Indian environment: implications for sustainable air quality management

Accurate prediction of fine particulate matter (PM2.5) remains challenging because atmospheric processes are nonlinear, nonstationary, and influenced by temporal variability, measurement uncertainty, and episodic pollution events. This study develops an interpretable and uncertainty-aware machine-learning (ML) framewor...