Resilient data-driven non-intrusive load monitoring for efficient energy management using machine learning techniques
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
1 Online-Ressource.
- Sprache
-
Englisch
- Erschienen in
-
Resilient data-driven non-intrusive load monitoring for efficient energy management using machine learning techniques ; volume:2024 ; number:1 ; day:11 ; month:5 ; year:2024 ; pages:1-21 ; date:12.2024
EURASIP journal on advances in signal processing / European Association for Speech, Signal and Image Processing ; 2024, Heft 1 (11.5.2024), 1-21, 12.2024
- Urheber
-
Nutakki, Mounica
Mandava, Srihari
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1186/s13634-024-01157-9
- URN
-
urn:nbn:de:101:1-2407221025588.394138723893
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:58 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
- Nutakki, Mounica
- Mandava, Srihari
- SpringerLink (Online service)
Ähnliche Objekte (12)
Data-driven models for crashworthiness optimisation: intrusive and non-intrusive model order reduction techniques
Non-intrusive load monitoring techniques for the disaggregation of ON/OFF appliances
Machine Learning for Non-Intrusive Load Monitoring
Non-intrusive data-driven ROM framework for hemodynamics problems
Non intrusive load monitoring for demand side management
Non-Intrusive Load Monitoring (NILM) : combining multiple distinct electrical features and unsupervised machine learning techniques
A brief review of reduced order models using intrusive and non‐intrusive techniques
Enhancing neural non-intrusive load monitoring with generative adversarial networks
A feature fusion technique for improved non-intrusive load monitoring
Perfednilm: a practical personalized federated learning-based non-intrusive load monitoring
Non-intrusive load monitoring and decomposition method based on decision tree
Appliance Event Detection for Non-Intrusive Load Monitoring in Complex Environments
Data-driven models for crashworthiness optimisation: intrusive and non-intrusive model order reduction techniques
Non-intrusive load monitoring techniques for the disaggregation of ON/OFF appliances
Machine Learning for Non-Intrusive Load Monitoring
Non-intrusive data-driven ROM framework for hemodynamics problems
Non intrusive load monitoring for demand side management
Non-Intrusive Load Monitoring (NILM) : combining multiple distinct electrical features and unsupervised machine learning techniques
A brief review of reduced order models using intrusive and non‐intrusive techniques
Enhancing neural non-intrusive load monitoring with generative adversarial networks
A feature fusion technique for improved non-intrusive load monitoring
Perfednilm: a practical personalized federated learning-based non-intrusive load monitoring
Non-intrusive load monitoring and decomposition method based on decision tree
Appliance Event Detection for Non-Intrusive Load Monitoring in Complex Environments
Data-driven models for crashworthiness optimisation: intrusive and non-intrusive model order reduction techniques
Non-intrusive load monitoring techniques for the disaggregation of ON/OFF appliances
Machine Learning for Non-Intrusive Load Monitoring
Non-intrusive data-driven ROM framework for hemodynamics problems
Non intrusive load monitoring for demand side management
Non-Intrusive Load Monitoring (NILM) : combining multiple distinct electrical features and unsupervised machine learning techniques
A brief review of reduced order models using intrusive and non‐intrusive techniques
Enhancing neural non-intrusive load monitoring with generative adversarial networks
A feature fusion technique for improved non-intrusive load monitoring
Perfednilm: a practical personalized federated learning-based non-intrusive load monitoring
Non-intrusive load monitoring and decomposition method based on decision tree