Analysis of Similarity Measures in Times Series Clustering for the Discovery of Building Energy Patterns

Analysis of Similarity Measures in Times Series Clustering for the Discovery of Building Energy Patterns

Forecasting and modeling building energy profiles require tools able to discover patterns within large amounts of collected information. Clustering is the main technique used to partition data into groups based on internal and a priori unknown schemes inherent of the data. The adjustment and paramet...

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Bibliographic Details
Main Authors: Wolfgang Kastner, Félix Iglesias
Format: Article
Language:English
Published: MDPI AG 2013-01-01
Series:Energies
Subjects:
clustering
time-series analysis
similarity measures
pattern discovery
building energy modeling
cluster validity
Online Access:http://www.mdpi.com/1996-1073/6/2/579

Internet

http://www.mdpi.com/1996-1073/6/2/579

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