Multi-Channel Recurrent Convolutional Neural Networks for Energy Disaggregation

Multi-Channel Recurrent Convolutional Neural Networks for Energy Disaggregation

Power consumption signals of household appliances are characterized by randomly occurring events (e.g. switch-on events), making timeseries modeling a demanding process. In this paper, we propose a convolutional neural network (CNN)-based architecture with inputs and outputs formed as data sequences...

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Bibliographic Details
Main Authors: Maria Kaselimi, Eftychios Protopapadakis, Athanasios Voulodimos, Nikolaos Doulamis, Anastasios Doulamis
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Convolutional neural network (CNN)
deep learning
energy disaggregation
load monitoring
NILM
power
Online Access:https://ieeexplore.ieee.org/document/8740964/

Internet

https://ieeexplore.ieee.org/document/8740964/

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