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
Time-Series based Household Electricity Consumption Forecas..:
, In:
2023 11th International Conference on Smart Grid (icSmartGrid)
,
Philips, Anita
;
Jayakumar, J.
- p. 1-15 , 2023
Link:
https://doi.org/10.1109/icSmartGrid58556.2023.10170973
RT T1 <cTitle>2023 11th International Conference on Smart Grid (icSmartGrid)</cTitle>: T1 <Title>Time-Series based Household Electricity Consumption Forecasting</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10170973&Exemplar=1&LAN=DE A1 Philips, Anita A1 Jayakumar, J. YR 2023 K1 Training K1 Energy consumption K1 Recurrent neural networks K1 Data analysis K1 Machine learning K1 Predictive models K1 Data models K1 Smart grids K1 Forecasting K1 Long short term memory SP 1 OP 15 LK http://dx.doi.org/https://doi.org/10.1109/icSmartGrid58556.2023.10170973 DO https://doi.org/10.1109/icSmartGrid58556.2023.10170973 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
