[HTML][HTML] Energetics Systems and artificial intelligence: Applications of industry 4.0
Industrial development with the growth, strengthening, stability, technical advancement,
reliability, selection, and dynamic response of the power system is essential. Governments …
reliability, selection, and dynamic response of the power system is essential. Governments …
NILM applications: Literature review of learning approaches, recent developments and challenges
This paper presents a critical approach to the non-intrusive load monitoring (NILM) problem,
by thoroughly reviewing the experimental framework of both legacy and state-of-the-art …
by thoroughly reviewing the experimental framework of both legacy and state-of-the-art …
Non-intrusive load monitoring: A review
PA Schirmer, I Mporas - IEEE Transactions on Smart Grid, 2022 - ieeexplore.ieee.org
The rapid development of technology in the electrical energy sector within the last 20 years
has led to growing electric power needs through the increased number of electrical …
has led to growing electric power needs through the increased number of electrical …
Transfer learning for non-intrusive load monitoring
M D'Incecco, S Squartini… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Non-intrusive load monitoring (NILM) is a technique to recover source appliances from only
the recorded mains in a household. NILM is unidentifiable and thus a challenge problem …
the recorded mains in a household. NILM is unidentifiable and thus a challenge problem …
NILM techniques for intelligent home energy management and ambient assisted living: A review
The ongoing deployment of smart meters and different commercial devices has made
electricity disaggregation feasible in buildings and households, based on a single measure …
electricity disaggregation feasible in buildings and households, based on a single measure …
An event-driven convolutional neural architecture for non-intrusive load monitoring of residential appliance
D Yang, X Gao, L Kong, Y Pang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Nowadays, the advancement of non-intrusive load monitoring (NILM) is hastened by the
everincreasing requirements for smart power utilization and demand side management …
everincreasing requirements for smart power utilization and demand side management …
Non-intrusive load monitoring and classification of activities of daily living using residential smart meter data
MA Devlin, BP Hayes - IEEE transactions on consumer …, 2019 - ieeexplore.ieee.org
This paper develops an approach for household appliance identification and classification of
household activities of daily living (ADLs) using residential smart meter data. The process of …
household activities of daily living (ADLs) using residential smart meter data. The process of …
[HTML][HTML] Non-intrusive load decomposition based on CNN–LSTM hybrid deep learning model
X Zhou, J Feng, Y Li - Energy Reports, 2021 - Elsevier
With the rapid development of science and technology, the problem of energy load
monitoring and decomposition of electrical equipment has been receiving widespread …
monitoring and decomposition of electrical equipment has been receiving widespread …
Unsupervised domain adaptation for nonintrusive load monitoring via adversarial and joint adaptation network
Nonintrusive load monitoring (NILM) is a technique to disaggregate an appliance's load
consumption from the aggregate load in a house. Monitoring the energy behavior has …
consumption from the aggregate load in a house. Monitoring the energy behavior has …
A low-rank learning-based multi-label security solution for industry 5.0 consumers using machine learning classifiers
The need for networking in smart industries known as Industry 5.0 has grown critical, and it
is especially important for the security and privacy of the applications. To counter threats to …
is especially important for the security and privacy of the applications. To counter threats to …