Artificial intelligence (AI) significantly enhances the development of Meta-Optics (MOs),
which encompasses advanced optical components like metalenses and metasurfaces …

Anomaly detection is indispensable for ensuring the reliable operation of grid-connected
photovoltaic (PV) systems. This study introduces a semi-supervised deep learning approach …

Efficient cooling systems are critical for maximizing the electrical efficiency of Photovoltaic
(PV) solar panels. However, conventional temperature probes often fail to capture the spatial …

The emergence of the coronavirus disease 2019 (COVID-19) pandemic has caused great
fear and panic around the world. In order to fight the COVID-19 virus, countries have had to …

Currently, fault identification in most photovoltaic systems primarily relies on experienced
engineers conducting on-site tests or interpreting data. However, due to limited human …

Diagnosing faults in a photovoltaic system using the Extra Trees ensemble algorithm Page 1
AIMS Energy, 12(4): 727–750. DOI: 10.3934/energy.2024034 Received: 26 February 2024 …

The quantity forecast of mobile subscribers requires accurate and reliable results for
obtaining insights into user trends and facilitating effective business management. Due to …

Photovoltaic (PV) installations have become integral for harnessing solar energy, yet
ensuring uninterrupted power generation remains crucial. This study addresses the …

Few-shot learning (FSL) is a learning paradigm which aims to address the issue of
machine/deep learning techniques which traditionally need huge amounts of labelled data …

The world's energy demand is on the rise, leading to an increased focus on renewable
energy options due to global warming and rising emissions from fossil fuels. To effectively …