I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
Enhanced Power System State Estimation Using Machine Learni..:
, In:
2023 International Conference on System Science and Engineering (ICSSE)
,
Huy, Truong Hoang Bao
;
Vo, Dieu Ngoc
;
Nguyen, Hung Duc
... - p. 401-405 , 2023
Link:
https://doi.org/10.1109/ICSSE58758.2023.10227147
RT T1 <cTitle>2023 International Conference on System Science and Engineering (ICSSE)</cTitle>: T1 <Title>Enhanced Power System State Estimation Using Machine Learning Algorithms</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10227147&Exemplar=1&LAN=DE A1 Huy, Truong Hoang Bao A1 Vo, Dieu Ngoc A1 Nguyen, Hung Duc A1 Truong, Hoa Phuoc A1 Dang, Khanh Tuan A1 Truong, Khoa Hoang YR 2023 SN 2325-0925 K1 Renewable energy sources K1 Machine learning algorithms K1 Correlation K1 Forestry K1 Power system stability K1 Stability analysis K1 Robustness K1 Power system state estimation K1 machine learning K1 deep learning K1 Random Forest K1 XGBoost SP 401 OP 405 LK http://dx.doi.org/https://doi.org/10.1109/ICSSE58758.2023.10227147 DO https://doi.org/10.1109/ICSSE58758.2023.10227147 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
