Comparison of short-term electrical load forecasting methods for different building types
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
2520-8942
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
online resource.
- Bibliographic citation
-
Comparison of short-term electrical load forecasting methods for different building types ; volume:4 ; number:3 ; day:13 ; month:9 ; year:2021 ; pages:1-16 ; date:9.2021
Energy informatics ; 4, Heft 3 (13.9.2021), 1-16, 9.2021
- Classification
-
Wirtschaft
- Creator
-
Groß, Arne
Lenders, Antonia
Schwenker, Friedhelm
Braun, Daniel A.
Fischer, David
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1186/s42162-021-00172-6
- URN
-
urn:nbn:de:101:1-2021112421581483997086
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:37 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Groß, Arne
- Lenders, Antonia
- Schwenker, Friedhelm
- Braun, Daniel A.
- Fischer, David
- SpringerLink (Online service)
Other Objects (12)
Short-Term Electrical Load Forecasting Based on Time Augmented Transformer
Power system short-term load forecasting
Probabilistic Short-Term Load Forecasting using conditioned normalizing flows
Electrical load forecasting using adaptive neuro-fuzzy inference system
Electrical load forecasting using adaptive neuro-fuzzy inference system
Real-time anomaly detection for very short-term load forecasting
Multiscale-integrated deep learning approaches for short-term load forecasting
Short-Term Electrical Load Forecasting Based on Fuzzy Rough Set Feature Selection and Multi-kernel Extreme Learning Machine
Modelling and forecasting short-term electricity load: a two step methodology
Graph Neural Network-Based Short‑Term Load Forecasting with Temporal Convolution
A Hybrid Model Equipped with the Minimum Cycle Decomposition Concept for Short-Term Forecasting of Electrical Load Time Series
Short-term load forecasting method based on fuzzy optimization combined model of load feature recognition
Short-Term Electrical Load Forecasting Based on Time Augmented Transformer
Power system short-term load forecasting
Probabilistic Short-Term Load Forecasting using conditioned normalizing flows
Electrical load forecasting using adaptive neuro-fuzzy inference system
Electrical load forecasting using adaptive neuro-fuzzy inference system
Real-time anomaly detection for very short-term load forecasting
Multiscale-integrated deep learning approaches for short-term load forecasting
Short-Term Electrical Load Forecasting Based on Fuzzy Rough Set Feature Selection and Multi-kernel Extreme Learning Machine
Modelling and forecasting short-term electricity load: a two step methodology
Graph Neural Network-Based Short‑Term Load Forecasting with Temporal Convolution
A Hybrid Model Equipped with the Minimum Cycle Decomposition Concept for Short-Term Forecasting of Electrical Load Time Series
Short-term load forecasting method based on fuzzy optimization combined model of load feature recognition
Short-Term Electrical Load Forecasting Based on Time Augmented Transformer
Power system short-term load forecasting
Probabilistic Short-Term Load Forecasting using conditioned normalizing flows
Electrical load forecasting using adaptive neuro-fuzzy inference system
Electrical load forecasting using adaptive neuro-fuzzy inference system
Real-time anomaly detection for very short-term load forecasting
Multiscale-integrated deep learning approaches for short-term load forecasting
Short-Term Electrical Load Forecasting Based on Fuzzy Rough Set Feature Selection and Multi-kernel Extreme Learning Machine
Modelling and forecasting short-term electricity load: a two step methodology
Graph Neural Network-Based Short‑Term Load Forecasting with Temporal Convolution
A Hybrid Model Equipped with the Minimum Cycle Decomposition Concept for Short-Term Forecasting of Electrical Load Time Series