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eNauka >  Rezultati >  Anomaly detection and classification in power system state estimation: Combining model-based and data-driven methods
Naziv: Anomaly detection and classification in power system state estimation: Combining model-based and data-driven methods
Autori: Asefi, Sajjad; Mitrovic, Mile; Cetenovic, Dragan N  ; Levi, Victor; Gryazina, Elena; Terzija, Vladimir
Godina: 2023
Publikacija: SUSTAINABLE ENERGY GRIDS & NETWORKS
ISSN: 2352-4677 Sustainable Energy Grids & Networks Pretraži identifikator
Izdavač: [Oxford] : Elsevier Ltd.
Tip rezultata: Naučni članak
Kolacija: vol. 35 str. 101116-101116
DOI: 10.1016/j.segan.2023.101116
WoS-ID: 001068747600001
Scopus-ID: 2-s2.0-85166961930
URI: https://enauka.gov.rs/handle/123456789/832261
Projekat: Skoltech
Ministry of Education and Science of Russian Federation [075-10-2021-067, 000000S707521QJX0002]
Engineering and Physical Sciences Research Council (EPSRC) of UK [EP/S00078X/2, EP/T021969/1]
Ministry of Science, Technological Development and In
Izvor metapodataka: (Preuzeto iz Nasi u WoS)
M-kategorija: 
21M21 - Vodeći međunarodni časopis kategorije M21

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