Time series distance-based methods for non-intrusive load monitoring in residential buildings

Kaustav Basu; Vincent Debusschere; Ahlame Douzal-Chouakria; Seddik Bacha

doi:10.1016/j.enbuild.2015.03.021

ScienceGate Book Chapters

JOURNAL ARTICLE

Time series distance-based methods for non-intrusive load monitoring in residential buildings

Kaustav Basu Vincent Debusschere Ahlame Douzal-Chouakria Seddik Bacha

Year: 2015 Journal: Energy and Buildings Vol: 96 Pages: 109-117 Publisher: Elsevier BV

DOI: 10.1016/j.enbuild.2015.03.021

Get Full-Text PDF Get Analytical Report

Keywords:

Hidden Markov model Smart meter Sampling (signal processing) Computer science Time series Data mining Domain (mathematical analysis) Time domain Sequence (biology) Series (stratigraphy) Duration (music) Data set Set (abstract data type) Real-time computing Engineering Artificial intelligence Machine learning Smart grid Mathematics Telecommunications

Metrics

Cited By

4.68

FWCI (Field Weighted Citation Impact)

Refs

0.96

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Smart Grid Energy Management

Physical Sciences → Engineering → Electrical and Electronic Engineering

Energy Load and Power Forecasting

Physical Sciences → Engineering → Electrical and Electronic Engineering

Data Stream Mining Techniques

Physical Sciences → Computer Science → Artificial Intelligence

Time series distance-based methods for non-intrusive load monitoring in residential buildings

Metrics

Citation History

Topics

Related Documents

Data for: Multivariate Event Detection Methods for Non Intrusive Load Monitoring in Residential Buildings

Multivariate event detection methods for non-intrusive load monitoring in smart homes and residential buildings

Feature extraction based hellinger distance algorithm for non-intrusive aging load identification in residential buildings

Residential Household Non-Intrusive Load Monitoring Using Multi-Label Classification Methods

Non-intrusive load monitoring based on MoCo_v2, time series self-supervised learning