Login
Register
Reset Password
Publish & Distribute
Publishing Solutions
Distribution Solutions
Subjects
Architecture and Design
Arts
Business and Economics
Chemistry
Classical and Ancient Near Eastern Studies
Computer Sciences
Cultural Studies
Engineering
General Interest
Geosciences
History
Industrial Chemistry
Jewish Studies
Law
Library and Information Science, Book Studies
Life Sciences
Linguistics and Semiotics
Literary Studies
Materials Sciences
Mathematics
Medicine
Music
Pharmacy
Philosophy
Physics
Social Sciences
Sports and Recreation
Theology and Religion
Publications
Journals
Books
Proceedings
Publishers
Blog
Contact
Search
EUR
USD
GBP
English
English
Deutsch
Polski
Español
Français
Italiano
Cart
Home
Journals
Applied Mathematics and Nonlinear Sciences
Volume 9 (2024): Issue 1 (January 2024)
Open Access
Generative Adversarial Network-based Data Recovery Method for Power Systems
Di Yang
Di Yang
,
Ming Ji
Ming Ji
,
Yuntong Lv
Yuntong Lv
,
Mengyu Li
Mengyu Li
and
Xuezhe Gao
Xuezhe Gao
| Jan 31, 2024
Applied Mathematics and Nonlinear Sciences
Volume 9 (2024): Issue 1 (January 2024)
About this article
Previous Article
Next Article
Abstract
References
Authors
Articles in this Issue
Preview
PDF
Cite
Share
Published Online:
Jan 31, 2024
Page range:
-
Received:
Dec 18, 2023
Accepted:
Dec 24, 2023
DOI:
https://doi.org/10.2478/amns-2024-0173
Keywords
PMU measurement data
,
LSTM-GAN
,
Hierarchical clustering
,
Power system clustering
,
System data recovery
© 2024 Di Yang et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.