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
An Adaptive Weight Ensemble Learning Method for Probabilist..:
, In:
2023 Panda Forum on Power and Energy (PandaFPE)
,
Lu, Liang
;
Zhou, Hong
;
Shen, Li
... - p. 1377-1381 , 2023
Link:
https://doi.org/10.1109/PandaFPE57779.2023.10141209
RT T1
2023 Panda Forum on Power and Energy (PandaFPE)
: T1
An Adaptive Weight Ensemble Learning Method for Probabilistic Wind Power Prediction
UL https://suche.suub.uni-bremen.de/peid=ieee-10141209&Exemplar=1&LAN=DE A1 Lu, Liang A1 Zhou, Hong A1 Shen, Li A1 Yang, Yuxiao A1 Wang, Qing A1 Yang, Yankun A1 Yang, Shiyou YR 2023 K1 Training K1 Uncertainty K1 Wind power generation K1 Probabilistic logic K1 Prediction algorithms K1 Regulation K1 Probability distribution K1 Probabilistic prediction K1 ensemble learning K1 data mining K1 correlation coefficients K1 wind power SP 1377 OP 1381 LK http://dx.doi.org/https://doi.org/10.1109/PandaFPE57779.2023.10141209 DO https://doi.org/10.1109/PandaFPE57779.2023.10141209 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)