Single-Phase Fault Detection Based on GCN-TCN Sparse-Attention Model-Reference-Cited by-同舟云学术

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Single-Phase Fault Detection Based on GCN-TCN Sparse-Attention Model

Published:2022-09-26 Issue: Volume: Page:
ISSN:
Container-title:2022 12th International Conference on Advanced Computer Information Technologies (ACIT)
language:
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Author:

Yong Ouyang¹,Dou Wan¹,Rong Gao²,Zhiwei Ye¹,Kochan Orest³

Affiliation:

1. Hubei University of Technology,School of Computer Science,China

2. Hubei University of Technology, Nanjing University,School of Computer Science, State Key Laboratory for Novel Software Technology,China

3. University Hubei University of Technology China,School of Computer Science Lviv Polytechnic National,Lviv,Ukraine

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9912736/9912739/09913084.pdf?arnumber=9913084

Reference35 articles.

1. Text Sentiment Classification Based on LSTM-TCN Hybrid Model and Attention Mechanism

2. Efficient Content-Based Sparse Attention with Routing Transformers

3. Short Term Wind Power Prediction Based on Wavelet Transform and BP Neural Network;s;Int Conf Green Commun Netw,2020

4. Prediction of time series using an analysis filter bank of LSTM unit;jose;Computers & Industrial Engineering,2021

5. A Hybrid Deep Learning Approach with GCN and LSTM for Traffic Flow Prediction*

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