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
Short-term load forecasting based on DenseNet-LSTM fusion m..:
, In:
2021 IEEE International Conference on Energy Internet (ICEI)
,
Liyun, Pan
;
Wenjun, Zhu
;
Sining, Wang
. - p. 84-89 , 2021
Link:
https://doi.org/10.1109/ICEI52466.2021.00021
RT T1
2021 IEEE International Conference on Energy Internet (ICEI)
: T1
Short-term load forecasting based on DenseNet-LSTM fusion model
UL https://suche.suub.uni-bremen.de/peid=ieee-9700994&Exemplar=1&LAN=DE A1 Liyun, Pan A1 Wenjun, Zhu A1 Sining, Wang A1 Lu, Han YR 2021 K1 Load forecasting K1 Computational modeling K1 Conferences K1 Time series analysis K1 Predictive models K1 Real-time systems K1 Power grids K1 DenseNet-LSTM K1 fusion model K1 prediction accuracy K1 short-term load forecasting SP 84 OP 89 LK http://dx.doi.org/https://doi.org/10.1109/ICEI52466.2021.00021 DO https://doi.org/10.1109/ICEI52466.2021.00021 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)