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
Application of Machine Learning Methods for Vector of RC St..:
, In:
2024 XXVII International Conference on Soft Computing and Measurements (SCM)
,
Tikhonova, Anna I.
;
Radabolsky, Vladislav S.
;
Mamedov, Geidar A.
.. - p. 368-372 , 2024
Link:
https://doi.org/10.1109/SCM62608.2024.10554201
RT T1 <cTitle>2024 XXVII International Conference on Soft Computing and Measurements (SCM)</cTitle>: T1 <Title>Application of Machine Learning Methods for Vector of RC States Analysis</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10554201&Exemplar=1&LAN=DE A1 Tikhonova, Anna I. A1 Radabolsky, Vladislav S. A1 Mamedov, Geidar A. A1 Gismelbari, Mohamed A. A1 Kosnevich, David A. YR 2024 K1 Accuracy K1 Navigation K1 Neural networks K1 Noise K1 Machine learning K1 Vectors K1 Stability analysis K1 robotic systems K1 state vector K1 Kalman filter K1 machine learning K1 neural network SP 368 OP 372 LK http://dx.doi.org/https://doi.org/10.1109/SCM62608.2024.10554201 DO https://doi.org/10.1109/SCM62608.2024.10554201 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
