A comprehensive analysis of the emerging modern trends in research on photovoltaic systems and desalination in the era of artificial intelligence and machine learning

Unlocking renewable energy potential: Harnessing machine learning and intelligent algorithms

“…Similar short-term variations and quick changes in meteorological conditions, which have a significant effect on solar PV generation and lead to inaccurate predictions, are also difficult for statistical techniques based on historical data patterns and statistical algorithms to capture (Antonopoulos and Antonopoulos, 2024;Marzouq et al, 2018; A. . ML models, on the other hand, can enhance accuracy by combining historical trends, incorporating real-time data, and adapting to changing circumstances (Jathar et al, 2024). ML-based methods work particularly well at identifying the connections between non-linear trends, which leads to more precise short-term solar PV projections.…”

Advancing reliability and efficiency of urban communication: Unmanned aerial vehicles, intelligent reflection surfaces, and deep learning techniques

“…Additionally, the papers in deduced time-varying parameters referring to angles of ‘arrival (AoAs) and ‘departure (AoDs) to effectively represent the channel's dynamic non-stationarity due to AI movement. Notably [ 13 ], focused solely on a single non-Line-of-Sight link and overlooked the mobility of scatterers. On a related note, delved into cluster-based propagation channels, while [ 14 ] extended the investigation to include initial azimuth, elevation, angle of arrival (AoA), and angle of departure (AoD) considerations.…”