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
Predicting Power Consumption Using Machine Learning Techniq..:
, In:
2024 International Wireless Communications and Mobile Computing (IWCMC)
,
Allal, Zaid
;
Noura, Hassan
;
Salman, Ola
. - p. 1522-1527 , 2024
Link:
https://doi.org/10.1109/IWCMC61514.2024.10592560
RT T1
2024 International Wireless Communications and Mobile Computing (IWCMC)
: T1
Predicting Power Consumption Using Machine Learning Techniques
UL https://suche.suub.uni-bremen.de/peid=ieee-10592560&Exemplar=1&LAN=DE A1 Allal, Zaid A1 Noura, Hassan A1 Salman, Ola A1 Vernier, Flavien YR 2024 SN 2376-6506 K1 Wireless communication K1 Power demand K1 Accuracy K1 Stacking K1 Predictive models K1 Planning K1 Steel K1 Machine Learning K1 Energy Consumption K1 Ensemble Learners K1 Sustainability K1 CO2 emissions K1 Resource Planning SP 1522 OP 1527 LK http://dx.doi.org/https://doi.org/10.1109/IWCMC61514.2024.10592560 DO https://doi.org/10.1109/IWCMC61514.2024.10592560 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)