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
Random-Forest Machine Learning Approach for High-Speed Rail..:
Gaoran Guo
;
Xuhao Cui
;
Bowen Du
https://www.mdpi.com/2076-3417/11/11/4756. , 2021
Link:
https://doi.org/10.3390/app11114756
RT Journal T1
Random-Forest Machine Learning Approach for High-Speed Railway Track Slab Deformation Identification Using Track-Side Vibration Monitoring
UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:ef1f699db13840c1916b05a4e99eb0da&Exemplar=1&LAN=DE A1 Gaoran Guo A1 Xuhao Cui A1 Bowen Du PB MDPI AG YR 2021 K1 HSR K1 track slab deformation K1 structural health monitoring K1 feature extraction K1 random-forest model K1 Technology K1 T K1 Engineering (General). Civil engineering (General) K1 TA1-2040 K1 Biology (General) K1 QH301-705.5 K1 Physics K1 QC1-999 K1 Chemistry K1 QD1-999 JF https://www.mdpi.com/2076-3417/11/11/4756 LK http://dx.doi.org/https://doi.org/10.3390/app11114756 DO https://doi.org/10.3390/app11114756 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)