Nonintrusive Load Monitoring Algorithm Using SOM-AdaDBSCAN-Reference-Cited by-同舟云学术

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Nonintrusive Load Monitoring Algorithm Using SOM-AdaDBSCAN

Published:2023-05-12 Issue: Volume: Page:
ISSN:
Container-title:2023 6th International Conference on Energy, Electrical and Power Engineering (CEEPE)
language:
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Author:

Xie Dongri¹,Fan Lipan¹,Fu Chen¹,Li Jing²,Nie Yongxin³,Liu Jun³

Affiliation:

1. Marketing Service Center (Measurement Center) State Grid Hubei Electric Power Co. Ltd,Wuhan,P.R. China

2. State Grid Hubei Comprehensive Energy Service Co. Ltd,Wuhan,P.R. China

3. School of Electrical Engineering Xi 'an Jiaotong University,Xi'an,P.R. China

Funder

Science and Technology Project

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10165683/10165687/10166637.pdf?arnumber=10166637

Reference20 articles.

1. Competitive Autoassociative Neural Networks for Electrical Appliance Identification for Non-Intrusive Load Monitoring

2. An intelligent nonintrusive load monitoring scheme based on 2D phase encoding of power signals

3. ADBSCAN: Adaptive Density-Based Spatial Clustering of Applications with Noise for Identifying Clusters with Varying Densities

4. Non-Intrusive Load Disaggregation Using Graph Signal Processing

5. Using neural networks for non-intrusive monitoring of industrial electrical loads

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