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A CGAN-based adversarial attack method for data-driven state estimation

With the development of data science and technology, the data-driven algorithms under the new power system architecture provide support for real-time and accurate state estimation (SE). However, the adoption of data-driven algorithms also introduces new security risks to power systems due to their i...

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Principais autores: Qi Wang, Jing Zhang, Jianxiong Hu, Shutan Wu, Shiyi Hou, Yi Tang
Formato: Artigo
Idioma:Inglês
Publicado em: Elsevier 2025-09-01
coleção:International Journal of Electrical Power & Energy Systems
Assuntos:
Adversarial attacks
Conditional generative adversarial networks
Data-driven algorithms
Generative adversarial networks
State estimation
Acesso em linha:http://www.sciencedirect.com/science/article/pii/S0142061525004260
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