2016
DOI: 10.1186/s40294-016-0020-0
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Complex building’s energy system operation patterns analysis using bag of words representation with hierarchical clustering

Abstract: Purpose Due to the large quantity of data that are recorded in energy efficient buildings, understanding the behavior of various underlying operations has become a complex and challenging task. This paper proposes a method to support analysis of energy systems and validates it using operational data from a cold water chiller. The method automatically detects various operation patterns in the energy system. Methods The use of k… Show more

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Cited by 12 publications
(5 citation statements)
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References 50 publications
(49 reference statements)
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“…In this manner, it shows significant advantages for time-series measures. 42,43 The studies in the building science field, like load transient recognition 44 and energy usage pattern recognition, 45 demonstrated that the shaped-based distance has a better performance. The formula of dynamic time warping (DTW) is shown in equation ( 5).…”
Section: Typical Energy Use Pattern Finding Modelmentioning
confidence: 99%
“…In this manner, it shows significant advantages for time-series measures. 42,43 The studies in the building science field, like load transient recognition 44 and energy usage pattern recognition, 45 demonstrated that the shaped-based distance has a better performance. The formula of dynamic time warping (DTW) is shown in equation ( 5).…”
Section: Typical Energy Use Pattern Finding Modelmentioning
confidence: 99%
“…No publication dealing with the description of biomass thermochemical transformation processes was found, especially not in terms of improving the quality of regulation of these processes. Furthermore, Habib et al (2016) has already observed the DTW method application to a general process control of building's energy systems.…”
Section: Use Of Dynamic Time Warping For Description Of Combustion Pr...mentioning
confidence: 99%
“…There are various methods available for outlier detection in data (Habib, Hayat, & Zucker, 2016;Habib, Zucker, Blochle, Judex, & Haase, 2015;Zucker, Habib, Blochle, Judex, & Leber, 2015). The combination of both Outlier Detection Algorithm (ODA) and J48 classifier gives quite accurate results (Devi & Devi, 2016).…”
Section: Malignant Cells Detection and Classificationsmentioning
confidence: 99%