Energy Science &Engineering, EarlyView.A novel cascade nanofluid‐based PV/T–TEG hybrid system (CS4) achieves 81.1% thermal and 18.75% exergy efficiency while cutting CO₂ emissions by 7.8 tons year⁻¹. The system delivers superior energy performance, economic savings, and environmental benefits, offering a sustainable pathway for next‐generation solar energy applications.
Abdelhak Lekbir +4 more
wiley +1 more source
Optimized Dual ANN Control Technique for Efficient Energy Management System (EMS) of Microgrid
Energy Science &Engineering, EarlyView.Proposed methodology. ABSTRACT The escalating global energy demand necessitates a shift towards sustainable and environmentally friendly alternatives. While renewable energy sources like solar and wind energy offer promising solutions, their intermittent nature poses significant challenges for grid integration.
Bin Li +5 more
wiley +1 more source
Artificial neural network based predictive modeling of viscosity of an oil based hybrid nanofluid. [PDF]
MethodsXFurqan M, Raees F, Khalid M.
europepmc +1 more source
Optimization of Energy Efficiency in Photovoltaic Water Pumping Systems Using Neural Networks
Energy Science &Engineering, EarlyView.This study investigates an optimal control strategy for a photovoltaic (PV) water pumping system aimed at improving efficiency and autonomy in off‐grid applications. The system uses an induction motor with direct torque control and compares three maximum power point tracking (MPPT) techniques: neural network–based MPPT, Incremental Conductance (IC ...
Sihem Ghoudelbourk +3 more
wiley +1 more source
A Hybrid Multi-Scale Transformer-CNN UNet for Crowd Counting. [PDF]
Sensors (Basel)Zhao K, He C, Peng S, Lu T.
europepmc +1 more source
Prediction of Pipeline Defect Depth and Classification Based on CatBoost
Energy Science &Engineering, EarlyView.Obtaining detection data using in‐line pipeline inspection, the synthetic minority oversampling technique (SMOTE) is applied to expand the sample set, thereby increasing the number of minority‐class samples. This approach effectively improves minority‐class detection and enhances pipeline safety assessment. ABSTRACT Magnetic flux leakage detection is a
Cong Chen +3 more
wiley +1 more source
"Smart agriculture: a climate-driven approach to modelling and forecasting fall armyworm populations in maize using machine learning algorithms". [PDF]
Front Plant SciKalisetti VS +9 more
europepmc +1 more source
Ensemble Deep Learning–Based Wind Power Forecasting With Self‐Adaptive Osprey Optimization Algorithm
Energy Science &Engineering, EarlyView.Design of Self‐Adaptive Osprey (SAO) algorithm: The novel SAO algorithm is designed by integrating the exploration capability of the conventional Osprey algorithm by including the self‐adaptiveness for enhancing the convergence rate. Ensemble Deep Learning for wind power forecasting: The wind forecasting is employed using the proposed Ensemble learning
Johncy Bai Johnson +3 more
wiley +1 more source
CLM-former for enhancing multi-horizon time series forecasting and load prediction in smart microgrids using a robust transformer-based model. [PDF]
Sci RepRahmatinia SM +2 more
europepmc +1 more source