Author

M. A. Raza

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Sep 2026

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.

Shakir Ali Soomro, N. H. Mirjat, K. Harijan et al. · Wind Engineering : The Inter... · 0 citations

Open access Jul 2026

Solar photovoltaic fault classifications under normal and shading conditions using machine learning models

This study suggested PV monitoring systems with lower maintenance costs and energy losses, and an accurate and efficient classifier for PV defects using normal and shading condition based on advanced ML techniques like Random Forest, K-Nearest Neighbors, Decision Tree, and SVM are proposed.

Aafaque Ali, M. A. Raza, Muneera Altayeb et al. · Discover Sustainability · 0 citations