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Applied Mathematics and Nonlinear Sciences
Volume 9 (2024): Issue 1 (January 2024)
Open Access
Deep Learning-based Network Security Protection for Scheduling Data in Power Plant Systems
Shengda Wang
Shengda Wang
JiLin Information & Telecommunication Company, State Grid Jilin Electric Power Corporation Ltd.
Changchun, China
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Wang, Shengda
,
Danni Liu
Danni Liu
JiLin Information & Telecommunication Company, State Grid Jilin Electric Power Corporation Ltd.
Changchun, China
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Liu, Danni
,
Chengliang Hao
Chengliang Hao
State Grid Jilin Electric Power Corporation Ltd.
Changchun, China
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Hao, Chengliang
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Li Cong
Li Cong
JiLin Information & Telecommunication Company, State Grid Jilin Electric Power Corporation Ltd.
Changchun, China
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Cong, Li
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Xiaofeng Xu
Xiaofeng Xu
State Grid Jilin Electric Power Corporation Ltd.
Changchun, China
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Xu, Xiaofeng
Jul 02, 2024
Applied Mathematics and Nonlinear Sciences
Volume 9 (2024): Issue 1 (January 2024)
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Published Online:
Jul 02, 2024
Received:
Mar 19, 2024
Accepted:
Jun 07, 2024
DOI:
https://doi.org/10.2478/amns-2024-1558
Keywords
<kwd>Deep learning</kwd>
,
<kwd>Peak density clustering algorithm</kwd>
,
<kwd>Control variable method</kwd>
,
<kwd>PSO</kwd>
,
<kwd>Bayesian attack graph</kwd>
,
<kwd>Network security defense</kwd>
© 2024 Shengda Wang et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
