A systematic review on imbalanced learning methods in intelligent fault diagnosis
The theoretical developments of data-driven fault diagnosis methods have yielded fruitful
achievements and significantly benefited industry practices. However, most methods are …
achievements and significantly benefited industry practices. However, most methods are …
[HTML][HTML] Ensemble LVQ Model for Photovoltaic Line-to-Line Fault Diagnosis Using K-Means Clustering and AdaGrad
Line-to-line (LL) faults are one of the most frequent short-circuit conditions in photovoltaic
(PV) arrays which are conventionally detected and cleared by overcurrent protection devices …
(PV) arrays which are conventionally detected and cleared by overcurrent protection devices …
[HTML][HTML] Voting based ensemble for detecting visual faults in photovoltaic modules using AlexNet features
NV Sridharan, S Vaithiyanathan, M Aghaei - Energy Reports, 2024 - Elsevier
This study proposes a novel approach utilizing a voting-based ensemble technique to
diagnose visible faults in photovoltaic (PV) modules from aerial images captured by …
diagnose visible faults in photovoltaic (PV) modules from aerial images captured by …
IHML: Incremental Heuristic Meta-Learner
O Karadeli, K Kaya… - Applied Artificial …, 2024 - Taylor & Francis
The landscape of machine learning constantly demands innovative approaches to enhance
algorithms' performance across diverse tasks. Meta-learning, known as “learning to learn” is …
algorithms' performance across diverse tasks. Meta-learning, known as “learning to learn” is …
A fault severity quantification approach of photovoltaic array based on pre-estimation and fine-tuning of fault parameters
J Zhang, Y Su, Y Liu, Z Yang, K Ding, Y Li… - Journal of Renewable …, 2023 - pubs.aip.org
Harsh outdoor operations may cause various abnormalities or faults of photovoltaic (PV)
array, decrease the energy yield and lifespan, and even cause catastrophic events …
array, decrease the energy yield and lifespan, and even cause catastrophic events …
Time-Frequency Image Representation Aided Deep Feature Extraction-Based Grid Connected Solar PV Fault Classification Framework
A Chakraborty, R Mandal, S Chatterjee - Applied Solar Energy, 2024 - Springer
Accurate detection of faults in grid connected solar PV systems is important to ensure the
reliability of power systems with distributed generation. Considering the aforesaid fact, here …
reliability of power systems with distributed generation. Considering the aforesaid fact, here …
Real Time PV fault detection in solar PV using Ensemble learning algorithm
R Priyadarshini, PS Manoharan… - … on Energy, Materials …, 2023 - ieeexplore.ieee.org
This This research proposes a technique to detect and classify defects in large-scale
photovoltaic (PV) systems, Adaptive boosting ensemble learning algorithms to achieve …
photovoltaic (PV) systems, Adaptive boosting ensemble learning algorithms to achieve …
Analysis and Application of Photovoltaic Grid Connection Optimization Model based on LightGBM Algorithm
J Huang, Y Che, Q Liang - 2024 International Conference on …, 2024 - ieeexplore.ieee.org
With the increasing popularity of photovoltaic (PV) energy worldwide, the operational
efficiency and stability of PV grid-connected systems have become critical issues that need …
efficiency and stability of PV grid-connected systems have become critical issues that need …
Optimization and application of artificial intelligence in robotic automated distribution network overhead line engineering
X Li, M Li, Y Tan, Y Wang - EAI Endorsed Transactions on Energy Web, 2023 - eudl.eu
INTRODUCTION: Artificial intelligence is a product of high-end technological development
since the 21st century, which has subverted people's traditional cognition in many aspects …
since the 21st century, which has subverted people's traditional cognition in many aspects …