Contextual Sequence-to-Point Deep Learning for Household Energy Disaggregation

Contextual Sequence-to-Point Deep Learning for Household Energy Disaggregation

This paper examines a contextual paradigm for energy disaggregation using Non-Intrusive Load Monitoring (NILM). Due to numerous issues including low sampling rates, missing data, misaligned readings, and diverse combinations of nonlinear and multi-state appliances, this problem is challenging and co...

Full description

Bibliographic Details
Main Authors: Mohammed Ayub, El-Sayed M. El-Alfy
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Smart metering
smart grid
smart buildings
deep learning
smart utility
energy disaggregation
Online Access:https://ieeexplore.ieee.org/document/10188822/

Internet

https://ieeexplore.ieee.org/document/10188822/

Similar Items