Shoaib Ahmed Khatri

A novel approach to multi-horizon wind speed forecasting based on advanced machine learning techniques using sparse meteorological data of indigenous wind farm of Pakistan

The results validate that ensemble learning models are more reliable for sparse Meteorological datasets, whereas DL models are effective for capturing short-term temporal patterns, and provides a practical forecasting framework for wind farms, offering improved operational planning, reduced forecasting uncertainty.