Search Results - univariate temporal convolutional denoising autoencoder (UTCN-DAE)

A Power System Disturbance Classification Method Robust to PMU Data Quality Issues.

Authors: Li, Zikang Liu, Hao Zhao, Junbo et al.

Source: IEEE Transactions on Industrial Informatics; Jan2022, Vol. 18 Issue 1, p130-142, 13p

A Data-Driven Convolutional Neural Network Approach for Power Quality Disturbance Signal Classification (DeepPQDS-FKTNet).

Authors: Saeed, Fahman Aldera, Sultan Alkhatib, Mohammad et al.

Source: Mathematics (2227-7390); Dec2023, Vol. 11 Issue 23, p4726, 15p

Subject Terms: CONVOLUTIONAL neural networks, SIGNAL classification, DEEP learning, FEATURE selection, DATABASES, ELECTRIC power distribution grids, PYRAMIDAL neurons

A Power System Disturbance Classification Method Robust to PMU Data Quality Issues

Authors: Zikang Li Hao Liu Junbo Zhao et al.

Source: IEEE Transactions on Industrial Informatics. 18:130-142

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://ieeexplore.ieee.org/document/9400766/
https://dblp.uni-trier.de/db/journals/tii/tii18.html#LiLZBY22

Ensemble learning based transmission line fault classification using phasor measurement unit (PMU) data with explainable AI (XAI).

Authors: Bin Akter, Simon Sarkar Pias, Tanmoy Rahman Deeba, Shohana et al.

Source: PLoS ONE; 2/12/2024, Vol. 19 Issue 2, p1-31, 31p

Subject Terms: PHASOR measurement, ELECTRIC lines, ARTIFICIAL intelligence, K-nearest neighbor classification, MAGNITUDE estimation, DEEP learning