has been cited by the following article(s):
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[1]
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Typical Scenario Load Identification Based on Feature Fusion and Transfer Learning
Recent Patents on Mechanical Engineering,
2025
DOI:10.2174/0122127976325514241001045948
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[2]
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Appliance Classification by Using Dynamic Voltage-Current Trajectory and 3D-Convolutional Neural Network
2024 Boao New Power System International Forum - Power System and New Energy Technology Innovation Forum (NPSIF),
2024
DOI:10.1109/NPSIF64134.2024.10883241
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[3]
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Non intrusive load identification method based on deep learning
3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023),
2023
DOI:10.1117/12.2685363
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[4]
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Non-Intrusive Load Monitoring by Load Trajectory and Multi-Feature Based on DCNN
IEEE Transactions on Industrial Informatics,
2023
DOI:10.1109/TII.2023.3240924
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[5]
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Noninvasive Load Identification Based on Combined Weighting-TOPSIS of Multifeature Fusion
Electric Power Components and Systems,
2023
DOI:10.1080/15325008.2023.2261119
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[6]
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A Classification and Identification Method for Overload of Network Big Data Based on Rels-Tsvm
2023 20th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP),
2023
DOI:10.1109/ICCWAMTIP60502.2023.10387042
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[7]
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A coarse-to-fine strategy based on a supervised learning method for non-intrusive load identification
2023 9th International Conference on Big Data Computing and Communications (BigCom),
2023
DOI:10.1109/BIGCOM61073.2023.00029
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[8]
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A non-invasive load identification method based on data association learning
2023 11th International Conference on Information Technology: IoT and Smart City (ITIoTSC),
2023
DOI:10.1109/ITIoTSC60379.2023.00012
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