Long-term system load forecasting based on data-driven linear clustering method
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
2196-5420
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
Long-term system load forecasting based on data-driven linear clustering method ; day:17 ; month:5 ; year:2017 ; pages:1-11
Journal of modern power systems and clean energy ; (17.5.2017), 1-11
- Klassifikation
-
Elektrotechnik, Elektronik
- Urheber
-
LI, Yiyan
- Beteiligte Personen und Organisationen
-
Han, Dong
Yan, Zheng
SpringerLink (Online service)
- DOI
-
10.1007/s40565-017-0288-x
- URN
-
urn:nbn:de:1111-201705266175
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:37 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- LI, Yiyan
- Han, Dong
- Yan, Zheng
- SpringerLink (Online service)
Ähnliche Objekte (12)
Ground-level ozone forecasting using data-driven methods
Indicators of economic crises: a data-driven clustering approach
Revenue forecasting in the mining industries: A data-driven approach
Data-driven surrogate model for wind turbine damage equivalent load
New Data-Driven Probabilistic Forecasting Methods with Applications in Energy Systems
Forecasting Chikungunya spread in the Americas via data-driven empirical approaches
Data-driven load profiles and the dynamics of residential electricity consumption
A real data-driven clustering approach for countries based on happiness score
Critical clusters in interdependent economic sectors : A data-driven spectral clustering analysis
Deriving Digital Energy Platform Archetypes for Manufacturing – A Data-Driven Clustering Approach
Data-driven decadal climate forecasting using Wasserstein time-series generative adversarial networks
Ideal point error for model assessment in data-driven river flow forecasting
Ground-level ozone forecasting using data-driven methods
Indicators of economic crises: a data-driven clustering approach
Revenue forecasting in the mining industries: A data-driven approach
Data-driven surrogate model for wind turbine damage equivalent load
New Data-Driven Probabilistic Forecasting Methods with Applications in Energy Systems
Forecasting Chikungunya spread in the Americas via data-driven empirical approaches
Data-driven load profiles and the dynamics of residential electricity consumption
A real data-driven clustering approach for countries based on happiness score
Critical clusters in interdependent economic sectors : A data-driven spectral clustering analysis
Deriving Digital Energy Platform Archetypes for Manufacturing – A Data-Driven Clustering Approach
Data-driven decadal climate forecasting using Wasserstein time-series generative adversarial networks
Ideal point error for model assessment in data-driven river flow forecasting
Ground-level ozone forecasting using data-driven methods
Indicators of economic crises: a data-driven clustering approach
Revenue forecasting in the mining industries: A data-driven approach
Data-driven surrogate model for wind turbine damage equivalent load
New Data-Driven Probabilistic Forecasting Methods with Applications in Energy Systems
Forecasting Chikungunya spread in the Americas via data-driven empirical approaches
Data-driven load profiles and the dynamics of residential electricity consumption
A real data-driven clustering approach for countries based on happiness score
Critical clusters in interdependent economic sectors : A data-driven spectral clustering analysis
Deriving Digital Energy Platform Archetypes for Manufacturing – A Data-Driven Clustering Approach
Data-driven decadal climate forecasting using Wasserstein time-series generative adversarial networks