Comparison of Machine Learning Techniques for the Detection of the Electricity Theft-Reference-Cited by-同舟云学术

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Comparison of Machine Learning Techniques for the Detection of the Electricity Theft

Published:2018-10 Issue: Volume: Page:
ISSN:
Container-title:2018 IEEE 3rd International Conference on Cloud Computing and Internet of Things (CCIOT)
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Author:

Gu Guodong,He Qingsu,Wang Bo,Dai Bo

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9027498/9032433/09032675.pdf?arnumber=9032675

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Electricity Theft Detection Using K-means Clustering in Electricity Information System;2024 International Conference on Smart Computing, IoT and Machine Learning (SIML);2024-06-06

2. Cyberattack detection for electricity theft in smart grids via stacking ensemble GRU optimization algorithm using federated learning framework;International Journal of Electrical Power & Energy Systems;2024-06

3. An Improved CNN Approach for Electricity Theft Detection;2023 China Automation Congress (CAC);2023-11-17

4. Data-driven intelligent method for detection of electricity theft;International Journal of Electrical Power & Energy Systems;2023-06

5. Evaluation of the Machine Learning Schemes for Information Security of Demand Response;2022 IEEE 6th Conference on Energy Internet and Energy System Integration (EI2);2022-11-11

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