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
MINDTwin AI: Multiphysics Informed Digital-Twin for Fault L..:
, In:
2023 International Conference on Big Data, Knowledge and Control Systems Engineering (BdKCSE)
,
Bashir, Amina
;
Mohsin, Muhammad Ahmed
;
Jazib, Muhammad
. - p. 1-8 , 2023
Link:
https://doi.org/10.1109/BdKCSE59280.2023.10339747
RT T1 <cTitle>2023 International Conference on Big Data, Knowledge and Control Systems Engineering (BdKCSE)</cTitle>: T1 <Title>MINDTwin AI: Multiphysics Informed Digital-Twin for Fault Localization in Induction Motor Using AI</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10339747&Exemplar=1&LAN=DE A1 Bashir, Amina A1 Mohsin, Muhammad Ahmed A1 Jazib, Muhammad A1 Iqbal, Hafsa YR 2023 K1 Location awareness K1 Analytical models K1 Induction motors K1 Computational modeling K1 Soft sensors K1 Real-time systems K1 Finite element analysis K1 Multiphysics K1 hybrid digital twin K1 finite element model K1 fault detection K1 Machine Learning K1 Deep neural network SP 1 OP 8 LK http://dx.doi.org/https://doi.org/10.1109/BdKCSE59280.2023.10339747 DO https://doi.org/10.1109/BdKCSE59280.2023.10339747 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
