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
Research on STLF Method Based on One-Dimensional Convolutio..:
, In:
2019 IEEE International Conference on Power Data Science (ICPDS)
,
Zeng, Qi
;
Pan, Haihui
;
Chen, Bin
. - p. 118-121 , 2019
Link:
https://doi.org/10.1109/ICPDS47662.2019.9017181
RT T1 <cTitle>2019 IEEE International Conference on Power Data Science (ICPDS)</cTitle>: T1 <Title>Research on STLF Method Based on One-Dimensional Convolution and Slope Feature</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9017181&Exemplar=1&LAN=DE A1 Zeng, Qi A1 Pan, Haihui A1 Chen, Bin A1 Liao, Zhifang YR 2019 K1 Convolution K1 Load modeling K1 Load forecasting K1 Predictive models K1 Machine learning K1 Analytical models K1 Neural networks K1 short-term load forecasting K1 deep learning K1 convolutional neural network K1 feature engineering SP 118 OP 121 LK http://dx.doi.org/https://doi.org/10.1109/ICPDS47662.2019.9017181 DO https://doi.org/10.1109/ICPDS47662.2019.9017181 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
