Data-Driven Climate Risk Forecasting Using Hybrid Machine Learning Models
This research proposes a new framework of analysis in predicting high-impact deviations in an environmental system in changing observational circumstances. The new approach, which is called Distribution-adaptive Uncertainty Synthesis (DAUS) is made to work without explicit physical assumptions or time-order-dependence,...