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Power Load Curve Clustering Algorithm Using Fast Dynamic Time Warping and Affinity Propagation

https://doi.org/10.1109/icsai.2018.8599336
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/9780470061190openalex-snapshot
Advances in Fuzzy Clustering and its Applications
inferredcites →https://doi.org/10.1007/978-3-540-68125-0_11openalex-snapshot
Accurate and Efficient Retrieval of Multimedia Time Series Data Under Uniform Scaling and Time Warping
inferredcites →https://doi.org/10.1007/bf01908075openalex-snapshot
Comparing partitions
inferredcites →https://doi.org/10.1007/s10115-004-0154-9openalex-snapshot
Exact indexing of dynamic time warping
inferredcites →https://doi.org/10.1016/j.enbuild.2016.03.047openalex-snapshot
Determining the relationship between a household’s lifestyle and its electricity consumption in Japan by analyzing measured electric load profiles
inferredcites →https://doi.org/10.1016/j.ijepes.2018.03.031openalex-snapshot
Clustering-based novelty detection for identification of non-technical losses
inferredcites →https://doi.org/10.1109/pedes.2014.7042027openalex-snapshot
A novel approach to design time of use tariff using load profiling and decomposition
inferredcites →https://doi.org/10.1109/tsg.2015.2409786openalex-snapshot
Analysis and Clustering of Residential Customers Energy Behavioral Demand Using Smart Meter Data
inferredcites →https://doi.org/10.1126/science.1136800openalex-snapshot
Clustering by Passing Messages Between Data Points
inferredcites →https://doi.org/10.3233/ida-2007-11508openalex-snapshot
Toward accurate dynamic time warping in linear time and space
inferredcites →https://doi.org/10.3390/en6020579openalex-snapshot
Analysis of Similarity Measures in Times Series Clustering for the Discovery of Building Energy Patterns
inferredcites →https://doi.org/10.5555/1756006.1953024openalex-snapshot
Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.3982129openalex-extracted
Selecting Representative Net Load Profiles of Solar Homes Using Clustering Techniques
inferred← citeshttps://doi.org/10.1007/s42452-026-08280-2openalex-snapshot
Improved hidden Markov-graph convolutional network energy decomposition algorithm for non-invasive load monitoring
inferred← citeshttps://doi.org/10.1016/j.rser.2022.112170openalex-snapshot
Optimized time reduction models applied to power and energy systems planning – Comparison with existing methods
inferred← citeshttps://doi.org/10.1088/1757-899x/646/1/012057openalex-snapshot
Research on Action Recognition Method Based on Weighted DTW Algorithm
inferred← citeshttps://doi.org/10.1109/infoteh68759.2026.11477761openalex-snapshot
Typical Load Profiles Definitions for Industrial Facilities Based on Energy Consumption Data Clustering
inferred← citeshttps://doi.org/10.2139/ssrn.5473443openalex-snapshot
Predicting Tracer Concentration Breakthrough Curves of Karst Springs by LSTM and Transformer Models
inferred← citeshttps://doi.org/10.3389/fmicb.2021.644012openalex-snapshot
Comparison of Methods for Picking the Operational Taxonomic Units From Amplicon Sequences
inferred← citeshttps://doi.org/10.35833/mpce.2020.000472openalex-snapshot
Electric Load Clustering in Smart Grid: Methodologies, Applications, and Future Trends
inferred← citeshttps://doi.org/10.47172/2965-730x.sdgsreview.v5.n09.pe07807openalex-snapshot
A Lossless-Compressed Time-Series Framework for Kinect-Based Handedness-Invariant Badminton Movement Analysis and Recognition (SDG 3: Good Health and Well-Being)
inferred← citeshttps://doi.org/10.70675/df483c9fzca84z4edbz9978z45be16061262openalex-snapshot
Essais sur la création d'une centrale électrique virtuelle pour les petites et moyennes entreprises
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