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Applied Mathematics and Nonlinear Sciences
Volume 9 (2024): Issue 1 (January 2024)
Open Access
Deep learning-based optimization method for detecting data anomalies in power usage detection devices
Hang Shang
Hang Shang
Department of Mechanical Engineering, College of Arts & Information Engineering, Dalian Polytechnic University
Dalian, China
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Shang, Hang
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Bing Bai
Bing Bai
Department of Mechanical Engineering, College of Arts & Information Engineering, Dalian Polytechnic University
Dalian, China
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Bai, Bing
,
Yang Mao
Yang Mao
Department of Mechanical Engineering, College of Arts & Information Engineering, Dalian Polytechnic University
Dalian, China
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Mao, Yang
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Jinhua Ding
Jinhua Ding
Department of Mechanical Engineering, College of Arts & Information Engineering, Dalian Polytechnic University
Dalian, China
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Ding, Jinhua
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Jiani Wang
Jiani Wang
Department of Mechanical Engineering, College of Arts & Information Engineering, Dalian Polytechnic University
Dalian, China
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Wang, Jiani
Sep 03, 2024
Applied Mathematics and Nonlinear Sciences
Volume 9 (2024): Issue 1 (January 2024)
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Published Online:
Sep 03, 2024
Received:
May 01, 2024
Accepted:
Jul 31, 2024
DOI:
https://doi.org/10.2478/amns-2024-2492
Keywords
<kwd>Graph Convolutional Neural Network</kwd>
,
<kwd>Migration Learning</kwd>
,
<kwd>Bayes’ Theorem</kwd>
,
<kwd>Hyper-parameter Optimization</kwd>
,
<kwd>Electricity Consumption Anomaly Detection</kwd>
© 2024 Hang Shang et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
