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Enhancing hydroelectric inflow prediction in the Brazilian power system: A comparative analysis of machine learning models and hyperparameter optimization for …
Electricity generation in Brazil heavily depends on hydroelectric power, making it vulnerable
to fluctuations due to its reliance on weather patterns. Accurately forecasting water inflow …
to fluctuations due to its reliance on weather patterns. Accurately forecasting water inflow …
Multi-scale split dual calibration network with periodic information for interpretable fault diagnosis of rotating machinery
Conventional intelligent fault diagnosis algorithms based on signal processing and pattern
recognition have high demands on expert experience and poor generalization performance …
recognition have high demands on expert experience and poor generalization performance …
Deep Learning in Industrial Machinery: A Critical Review of Bearing Fault Classification Methods
The review provides an overview of the state-of-the-art in Deep Learning (DL) algorithms for
rolling bearing fault classification which remains vital in industrial sectors including …
rolling bearing fault classification which remains vital in industrial sectors including …
[HTML][HTML] A communication-less islanding detection scheme for hybrid distributed generation systems using recurrent neural network
The proposed scheme in this research paper is a communication-less islanding detection
system based on recurrent neural network (RNN) for hybrid distributed generator (DG) …
system based on recurrent neural network (RNN) for hybrid distributed generator (DG) …
A cross-domain intelligent fault diagnosis method based on deep subdomain adaptation for few-shot fault diagnosis
Most existing cross-domain intelligent fault diagnosis algorithms rely on many samples and
only consider the global alignment of all faults. It is not practical to obtain numerous fault …
only consider the global alignment of all faults. It is not practical to obtain numerous fault …
Semantic segmentation-based intelligent threshold-free feeder detection method for single-phase ground fault in distribution networks
Feeder detection for single-phase ground fault (SPGF) is challenging in a resonant
grounded system due to the difference in feeder capacitance to ground and the influence of …
grounded system due to the difference in feeder capacitance to ground and the influence of …
Faulty-feeder detection for single phase-to-ground faults in distribution networks based on waveform encoding and waveform segmentation
Faulty feeder detection helps ensure the stability and safety of power grids after single-
phase-to-ground (SPG) faults occur in distribution networks. The existing detection …
phase-to-ground (SPG) faults occur in distribution networks. The existing detection …
Fault diagnosis of highway machinery hydraulic system based on LS-TF
Fault diagnosis of hydraulic system is of great significance to reduce the risk of damage to
road machinery and improve construction safety. The hydraulic system of highway …
road machinery and improve construction safety. The hydraulic system of highway …
High impedance fault classification in microgrids using a transformer-based model with time series harmonic synchrophasors under data quality issues
Recent advances in distribution networks, driven by the integration of renewable energy
sources, have spurred the emergence of microgrids, elevating concerns regarded reliability …
sources, have spurred the emergence of microgrids, elevating concerns regarded reliability …
[HTML][HTML] Faulty feeder selection based on improved Hough transform in resonant grounded distribution networks
X Wang, X Qu, L Guo, Z Zhang, Y Wang… - International Journal of …, 2024 - Elsevier
Due to the weak fault characteristics and inaccurate fault line selection during high
impedance faults, this paper proposes a new method for fault line selection in resonant …
impedance faults, this paper proposes a new method for fault line selection in resonant …