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Open Access

Peer-reviewed

Research Article

A new method for identifying a fault in T-connected lines based on multiscale S-transform energy entropy and an extreme learning machine

Hao Wu ,

Roles Funding acquisition, Project administration, Writing – original draft

* E-mail: wuhao801212@163.com

Affiliation Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Zigong, China

http://orcid.org/0000-0002-9799-9855

⨯
Jie Yang,

Roles Data curation, Methodology, Writing – review & editing

Affiliation Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Zigong, China
⨯
Leilei Chen,

Roles Formal analysis, Software

Affiliation Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Zigong, China
⨯
Qiaomei Wang

Roles Formal analysis, Visualization

Affiliation Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Zigong, China
⨯

A new method for identifying a fault in T-connected lines based on multiscale S-transform energy entropy and an extreme learning machine

Hao Wu,
Jie Yang,
Leilei Chen,
Qiaomei Wang

x

Published: August 15, 2019
https://doi.org/10.1371/journal.pone.0220870

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