Mar 24, 2024 · Our research proposes a novel anomaly detection system for power grids that prevents overfitting. We created a network graph to represent the ...
We combine the capabilities of Long Short-Term Memory. (LSTM) models with a Graph Isomorphism Network (GIN) in a hybrid model to pinpoint anomalies in the grid.
Oct 22, 2024 · We created a network graph to represent the structure of the power grid, where nodes represent power grid components like generators and edges ...
Amelia Jobe is an undergraduate student at Boise State University ... Power Grid Anomaly Detection via Hybrid LSTM-GIN Model (Student Abstract) | VIDEO.
Power Grid Anomaly Detection via Hybrid LSTM-GIN Model (Student Abstract). AAAI 2024: 23525-23527. [+][–]. Coauthor network. maximize. Note that this feature is ...
We combine the capabilities of Long Short-Term Memory (LSTM) models with a Graph Isomorphism Network (GIN) in a hybrid model to pinpoint anomalies in the grid.
We combine the capabilities of Long Short-Term Memory (LSTM) models with a Graph Isomorphism Network (GIN) in a hybrid model to pinpoint anomalies in the grid.
Power Grid Anomaly Detection via Hybrid LSTM-GIN Model (Student Abstract) · Engineering, Computer Science. AAAI Conference on Artificial Intelligence · 2024.
Power Grid Anomaly Detection via Hybrid LSTM-GIN Model (Student Abstract) | VIDEO. AAAI 2024. +3. RK. AD. Amelia Jobe and 5 other authors. 23 February ...