South Korean researchers have developed a guided-learning framework that accurately predicts PV power without requiring irradiance sensors during operation, using routine meteorological data instead.
A machine learning model trained on EEG data from patients recovering from strokes helps predict how new patients will regain ...
The model predicts RNA decay rates (stability) in breast cancer cell lines, achieving correlation of ~0.62 on test data. GreyHound/ ├── src/ # Core model implementation │ ├── greyhound.py # Main model ...
Vehicle trajectory prediction plays a vital role in intelligent transportation systems and autonomous driving, as it significantly affects vehicle behavior planning and control, thereby influencing ...
Abstract: This paper presents an original application of physics-informed neural networks (PINN) to the problem of computing the critical clearing time in power system rotor-angle transient stability ...
Constrained by the overcurrent capacity of semiconductor components, grid-forming (GFM) converters need to switch from constant-voltage control (CVC) mode to current-limiting control (CLC) mode during ...
Abstract: The generalized Hamiltonian system theory (GHST) is a powerful tool for excitation control in high-dimensional non-linear power systems, but relies on reduced-order dynamics, given the ...
1 Guangdong Power Grid Corporation Foshan Power Supply Bureau, Foshan, China 2 Electric Power Research Institute of China Southern Power Grid, Guangzhou, Guangdong, China Introduction: The escalating ...
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