Cargando…

DiffNILM: A Novel Framework for Non-Intrusive Load Monitoring Based on the Conditional Diffusion Model

Non-intrusive Load Monitoring (NILM) is a critical technology that enables detailed analysis of household energy consumption without requiring individual metering of every appliance, and has the capability to provide valuable insights into energy usage behavior, facilitate energy conservation, and o...

Descripción completa

Detalles Bibliográficos
Autores principales:	Sun, Ruichen, Dong, Kun, Zhao, Jianfeng
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2023
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10099094/ https://www.ncbi.nlm.nih.gov/pubmed/37050600 http://dx.doi.org/10.3390/s23073540

Ejemplares similares

Smart Distribution Boards (Smart DB), Non-Intrusive Load Monitoring (NILM) for Load Device Appliance Signature Identification and Smart Sockets for Grid Demand Management
por: Kerk, See Gim, et al.
Publicado: (2020)

Exploiting Smart Meter Power Consumption Measurements for Human Activity Recognition (HAR) with a Motif-Detection-Based Non-Intrusive Load Monitoring (NILM) Approach
por: Wilhelm, Sebastian, et al.
Publicado: (2021)

A NILM load identification method based on structured V-I mapping
por: Du, Zehua, et al.
Publicado: (2023)

Non-Intrusive Load Monitoring
por: Fortuna, Luigi, et al.
Publicado: (2022)

Med-cDiff: Conditional Medical Image Generation with Diffusion Models
por: Hung, Alex Ling Yu, et al.
Publicado: (2023)

Multi-State Energy Classifier to Evaluate the Performance of the NILM Algorithm
por: Desai, Sanket, et al.
Publicado: (2019)

Non-intrusive load monitoring: theory, technologies and applications
por: Liu, Hui
Publicado: (2020)

ELECTRIcity: An Efficient Transformer for Non-Intrusive Load Monitoring
por: Sykiotis, Stavros, et al.
Publicado: (2022)

A New NILM System Based on the SFRA Technique and Machine Learning
por: Mari, Simone, et al.
Publicado: (2023)

Apply Graph Signal Processing on NILM: An Unsupervised Approach Featuring Power Sequences †
por: Zhao, Bochao, et al.
Publicado: (2023)

DiffCircaPipeline: a framework for multifaceted characterization of differential rhythmicity
por: Xue, Xiangning, et al.
Publicado: (2023)

Non-Intrusive Load Monitoring of Buildings Using Spectral Clustering
por: Ghaffar, Muzzamil, et al.
Publicado: (2022)

Deep Learning-Based Non-Intrusive Commercial Load Monitoring
por: Zhou, Mengran, et al.
Publicado: (2022)

TnseqDiff: identification of conditionally essential genes in transposon sequencing studies
por: Zhao, Lili, et al.
Publicado: (2017)

A synthetic energy dataset for non-intrusive load monitoring in households
por: Klemenjak, Christoph, et al.
Publicado: (2020)

Deep Adaptive Ensemble Filter for Non-Intrusive Residential Load Monitoring
por: Kianpoor, Nasrin, et al.
Publicado: (2023)

On enabling collaborative non-intrusive load monitoring for sustainable smart cities
por: Shi, Yunchuan, et al.
Publicado: (2023)

The fractal nature of Riem/Diff I
por: Nabutovsky, A, et al.
Publicado: (2000)

Quantum vortices and Diff (R$^{3}$)
por: Rasetti, M, et al.
Publicado: (1984)

Interpolation and Amalgamation for Arrays with MaxDiff
por: Ghilardi, Silvio, et al.
Publicado: (2021)

Non-Intrusive Load Monitoring Approaches for Disaggregated Energy Sensing: A Survey
por: Zoha, Ahmed, et al.
Publicado: (2012)

Assessing Human Activity in Elderly People Using Non-Intrusive Load Monitoring
por: Alcalá, José M., et al.
Publicado: (2017)

A Semi-Supervised Approach for Improving Generalization in Non-Intrusive Load Monitoring
por: Pujić, Dea, et al.
Publicado: (2023)

Conference Formal and Analytic Solutions of Diff. Equations
por: Filipuk, Galina, et al.
Publicado: (2018)

Power-Based Non-Intrusive Condition Monitoring for Terminal Device in Smart Grid †
por: Zhang, Guoming, et al.
Publicado: (2020)

Non-Intrusive Load Monitoring for Residential Appliances with Ultra-Sparse Sample and Real-Time Computation
por: Hu, Minzheng, et al.
Publicado: (2021)

Toward Robust Non-Intrusive Load Monitoring via Probability Model Framed Ensemble Method
por: Liu, Yu, et al.
Publicado: (2021)

Rule-Based Non-Intrusive Load Monitoring Using Steady-State Current Waveform Features
por: Shareef, Hussain, et al.
Publicado: (2023)

DiffLogo: a comparative visualization of sequence motifs
por: Nettling, Martin, et al.
Publicado: (2015)

MetaboDiff: an R package for differential metabolomic analysis
por: Mock, Andreas, et al.
Publicado: (2018)

Privacy-preserving household load forecasting based on non-intrusive load monitoring: A federated deep learning approach
por: Zhou, Xinxin, et al.
Publicado: (2022)

Non-intrusive Quality Analysis of Monitoring Data
por: Brightwell, M, et al.
Publicado: (2010)

lncDIFF: a novel quasi-likelihood method for differential expression analysis of non-coding RNA
por: Li, Qian, et al.
Publicado: (2019)

Towards Trustworthy Energy Disaggregation: A Review of Challenges, Methods, and Perspectives for Non-Intrusive Load Monitoring
por: Kaselimi, Maria, et al.
Publicado: (2022)

The Copenhagen Primary Care Differential Count (CopDiff) database
por: Andersen, Christen Lykkegaard, et al.
Publicado: (2014)

diff_classifier: Parallelization of multi-particle tracking video analyses
por: Curtis, Chad, et al.
Publicado: (2019)

Streamlining differential exon and 3′ UTR usage with diffUTR
por: Gerber, Stefan, et al.
Publicado: (2021)

A Bayesian Approach to Unsupervised, Non-Intrusive Load Disaggregation
por: Massidda, Luca, et al.
Publicado: (2022)

A Non-Intrusive Method for Monitoring the Degradation of MOSFETs
por: Wu, Li-Feng, et al.
Publicado: (2014)

Workshop on Intrusion Detection and Network Monitoring
por: USENIX Association. Berkeley
Publicado: (1999)

Cannot write session to /tmp/vufind_sessions/sess_l7b3561qqol5acs8g9rhbcurrk