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Author

T. A. Jumani

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Open access Oct 2026

Lite-BiAttn: A Lightweight CNN-BiLSTM Attention Model for Accurate Solar Radiation Forecasting

Reliable short-term prediction of global horizontal irradiance (GHI) is essential for maximizing photovoltaic (PV) power generation, improving grid reliability, and enabling efficient integration of renewable energy sources. This study proposes Lite-BiAttn, a lightweight hybrid deep learning framework that combines one...

Shiraz Afzal, Farrukh Hafeez, A. Nahhas et al. · 0 citations
Open access Sep 2026

Integrated Data-Driven Framework for Rooftop PV Impact Assessment in Distribution Networks Using Net-Load Forecasting and Hosting Capacity Analysis

The increasing use of rooftop photovoltaic (PV) systems in distribution networks can lead to operational challenges, including feeder overloading, reverse power flow, fluctuating net-load characteristics, and future hosting-capacity constraints. This research presents an integrated data-driven approach for the holistic...

Mohamed Shaik Honnurvali, Badar Ali Al Washahi, Mazhar Baloch et al. · 0 citations
Open access Aug 2026

A Coordinated Control-Based Power Management Strategy for a Hybrid Solar–Wind–Battery Integrated Standalone DC Microgrid for Rural Electrification

Standalone DC microgrids offer a promising solution for providing reliable and sustainable electricity to remote communities in developing countries. However, the intermittent nature of solar and wind resources, combined with continuously varying load demand, presents considerable operational challenges in maintaining...

S. Memon, P. Shaikh, Z. Memon et al. · 0 citations
Open access Sep 2026

Attention-Enhanced CNN–BiLSTM Framework with Temporal Feature Engineering for Global Horizontal Irradiance Forecasting

The proposed CNN–BiLSTM–Attention framework performed better than conventional benchmark models of machine learning and deep learning, achieving a Root Mean Square Error of 0.088 and Seasonal and atmospheric-condition evaluations also showed consistent performance across different seasonal and atmospheric conditions.

Farrukh Hafeez, T. Jumani, Z. Arfeen et al. · 0 citations
Open access 2026

Solar-Powered IoT–ML Framework for Energy-Aware Crop Suitability Prediction

By integrating solar-powered IoT infrastructure with ML-based analytics, class-imbalance handling, and computational-efficiency evaluation, the proposed framework offers a practical and scalable solution for energy-aware suitability assessment in resource-constrained farming environments.

Yusra Mansoor, Huma Jamshed, M. Khouj et al. · 0 citations
Open access Aug 2026

Particle Swarm Optimization-Based Feature Weighting and Early-Cycle Remaining Useful Life Prediction of Lithium-Ion Batteries

A machine learning framework using particle swarm optimization (PSO) to perform hyperparameter tuning and feature optimization to improve lithium-ion battery RUL prediction and offers a highly interpretable and effective solution for predicting lithium-ion battery RUL.

Matee Ur Rasool, Abdul Salam, M. Masud et al. · 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. · 0 citations

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