A Nonintrusive Load Identification Method Based on Dual-Branch Attention GRU Fusion Network
Author:
Affiliation:
1. College of Big Data and Software Engineering, Zhejiang Wanli University, Ningbo, Zhejiang, China
2. School of Engineering, Hangzhou Normal University, Hangzhou, Zhejiang, China
Funder
Natural Science Foundation of Ningbo City
School Foundation of Zhejiang Wanli University
Key Laboratory of Film and TV Media Technology of Zhejiang Province
Open Project Program of the State Key Laboratory of Computer-Aided Design&Computer Graphics (CAD&CG) of Zhejiang University
General Scientific Research Project of Zhejiang Provincial Department of Education
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/19/10367905/10565840.pdf?arnumber=10565840
Reference36 articles.
1. Nonintrusive appliance load monitoring
2. A Time Efficient Factorial Hidden Markov Model-Based Approach for Non-Intrusive Load Monitoring
3. Non-intrusive load monitoring by using active and reactive power in additive Factorial Hidden Markov Models
4. A Novel Current Signal Feature and Its Application in Noninvasive Load Monitoring
5. Non-intrusive Load Monitoring Based on the Graph Least Squares Reconstruction Method
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