A Data Distillation Enhanced Autoencoder for Detecting Anomalous Gas Consumption-Reference-Cited by-同舟云学术

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A Data Distillation Enhanced Autoencoder for Detecting Anomalous Gas Consumption

Published:2023 Issue: Volume: Page:1-1
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Zhou Yujue¹^ORCID,Jiang Jie²,Yang Shuang-Hua³^ORCID,He Ligang⁴^ORCID,Ding Yulong³^ORCID,Liu Kai³,Zhu Guozhong⁵,Qing Yali⁵

Affiliation:

1. National Pilot School of Software, Yunnan University, Kunming, China

2. Department of Artificial Intelligence, China University of Petroleum-Beijing, Beijing, P.R. China

3. Shenzhen Key Laboratory of Safety and Security for Next Generation of Industrial Internet, Southern University of Science and Technology, Shenzhen, China

4. Department of Computer Science, University of Warwick, Coventry, UK

5. Shenzhen Gas, Shenzhen, P.R. China

Funder

National Natural Science Foundation of China

Department of Education of Guangdong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/6702522/10185960.pdf?arnumber=10185960

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