Low frequency residential non-intrusive load monitoring based on a hybrid feature extraction tree-learning approach-Reference-Cited by-同舟云学术

Low frequency residential non-intrusive load monitoring based on a hybrid feature extraction tree-learning approach

Published:2022-03-12 Issue:1 Volume:44 Page:493-514
ISSN:1556-7036
Container-title:Energy Sources, Part A: Recovery, Utilization, and Environmental Effects
language:en
Short-container-title:Energy Sources, Part A: Recovery, Utilization, and Environmental Effects

Author:

Timplalexis Christos¹^ORCID,Angelis Georgios-Fotios¹^ORCID,Krinidis Stelios¹²^ORCID,Ioannidis Dimosthenis¹^ORCID,Tzovaras Dimitrios¹^ORCID

Affiliation:

1. Centre for Research and Technology Hellas, Information Technologies Institute, Thessaloniki, Greece

2. School of Economics and Business Administration, Management Science and Technology Department, International Hellenic University (Ihu), Thessaloniki, Greece

Publisher

Informa UK Limited

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Link

https://www.tandfonline.com/doi/pdf/10.1080/15567036.2022.2046663

Reference64 articles.

1. Generative Adversarial Networks and Transfer Learning for Non-Intrusive Load Monitoring in Smart Grids

2. Application of wavelet-based ensemble tree classifier for non-intrusive load monitoring

3. It's Different

4. NILMTK

5. The ECO data set and the performance of non-intrusive load monitoring algorithms

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