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 Convolution Neural Network to Gas Turbine Ga..:
, In:
Proceedings of the 2023 International Conference on Big Data Mining and Information Processing
,
Yang, Qingcai
;
Wang, Liang
;
Yao, Wendan
... - p. 138-148 , 2023
Link:
https://dl.acm.org/doi/10.1145/3645279.3645304
RT T1 <cTitle>Proceedings of the 2023 International Conference on Big Data Mining and Information Processing</cTitle>: T1 <Title>Application of Convolution Neural Network to Gas Turbine Gas Path Fault Diagnosis</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3645304&Exemplar=1&LAN=DE A1 Yang, Qingcai A1 Wang, Liang A1 Yao, Wendan A1 Chen, Hongbo A1 Jing, Hongkai A1 Li, Ning PB ACM YR 2023 K1 convolution neural network K1 data-driven K1 fault diagnosis K1 gas path fault K1 gas turbine K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Neural networks K1 Applied computing K1 Physical sciences and engineering K1 Engineering SP 138 OP 148 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3645279.3645304 DO https://dl.acm.org/doi/10.1145/3645279.3645304 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
