Prognostics and health management of photovoltaic systems based on deep learning: A state-of-the-art review and future perspectives
As global photovoltaic (PV) power generation capacity rapidly expands, efficient and
effective health management of PV systems has emerged as a critical focal point. With the …
effective health management of PV systems has emerged as a critical focal point. With the …
Machine learning applications in health monitoring of renewable energy systems
Rapidly evolving renewable energy generation technologies and the ever-increasing scale
of renewable energy installations are driving the need for more accurate, faster, and smarter …
of renewable energy installations are driving the need for more accurate, faster, and smarter …
Feature extraction and fault diagnosis of photovoltaic array based on current–voltage conversion
Fault diagnosis plays a crucial role in the operation and maintenance (O&M) of photovoltaic
(PV) arrays, and reasonable feature extraction is a prerequisite for effective fault diagnosis …
(PV) arrays, and reasonable feature extraction is a prerequisite for effective fault diagnosis …
A method for accurate prediction of photovoltaic power based on multi-objective optimization and data integration strategy
G Li, X Wei, H Yang - Applied Mathematical Modelling, 2024 - Elsevier
Reliable photovoltaic power prediction is crucial to power dispatching and power grid
management. Aiming at the problems that the existing photovoltaic power prediction has low …
management. Aiming at the problems that the existing photovoltaic power prediction has low …
A multimodal learning machine framework for Alzheimer's disease diagnosis based on neuropsychological and neuroimaging data
M Zhang, Q Cui, Y Lü, W Yu, W Li - Computers & Industrial Engineering, 2024 - Elsevier
Alzheimer's disease (AD) is the most prevalent form of dementia, with no current cure. Early
screening and intervention are vital. In multimodal AD data, besides neuroimaging …
screening and intervention are vital. In multimodal AD data, besides neuroimaging …
[HTML][HTML] Artificial intelligence techniques for ground fault line selection in power systems: State-of-the-art and research challenges
F Wang, Z Zhang, K Wu, D Jian, Q Chen… - Mathematical …, 2023 - aimspress.com
In modern power systems, efficient ground fault line selection is crucial for maintaining
stability and reliability within distribution networks, especially given the increasing demand …
stability and reliability within distribution networks, especially given the increasing demand …
Artificial neural network based optimization for Ag grated D-shaped optical fiber surface plasmon resonance refractive index sensor
This study reports the optimization of fiber optic SPR refractive index sensor parameters with
the simulation of finite element method (FEM) and artificial neural network (ANN) model. To …
the simulation of finite element method (FEM) and artificial neural network (ANN) model. To …
Automatic fault detection of utility-scale photovoltaic solar generators applying aerial infrared thermography and orthomosaicking
As large-scale Photovoltaic (PV) power plants are being expanded in installation number
and capacity, aerial infrared thermography (aIRT) has proven to be effective in detecting at …
and capacity, aerial infrared thermography (aIRT) has proven to be effective in detecting at …
[HTML][HTML] Bearings faults and limits in wind turbine generators
RMA Velásquez - Results in Engineering, 2024 - Elsevier
The detection of sudden faults in wind turbine generator (WTG) is a complex task, especially
in bearings. Usually, the evaluation of methodologies such as vibration, ultrasound, and …
in bearings. Usually, the evaluation of methodologies such as vibration, ultrasound, and …
Evolutionary ensembles based on prioritized aggregation operator
Ensemble methods are advanced learning algorithm proposed for generating base
classifiers and accumulating them all together to derive a new classifier which is expected to …
classifiers and accumulating them all together to derive a new classifier which is expected to …