The Community for Technology Leaders
2015 13th International Conference on Frontiers of Information Technology (FIT) (2015)
Islamabad, Pakistan
Dec. 14, 2015 to Dec. 16, 2015
ISBN: 978-1-4673-9665-3
pp: 303-308
The understanding of the buildings operation has become a challenging task due to the large amount of data recorded in energy efficient buildings. Still, today the experts use visual tools for analyzing the data. In order to make the task realistic, a method has been proposed in this paper to automatically detect the different patterns in buildings. The K Means clustering is used to automatically identify the ON (operational) cycles of the chiller. In the next step the ON cycles are transformed to symbolic representation by using Symbolic Aggregate Approximation (SAX) method. Then the SAX symbols are converted to bag of words representation for hierarchical clustering. Moreover, the proposed technique is applied to real life data of adsorption chiller. Additionally, the results from the proposed method and dynamic time warping (DTW) approach are also discussed and compared.
Buildings, Time series analysis, Adsorption, Aggregates, Clustering algorithms, Cooling, Temperature sensors,Coefficient of Performance (COP), Building energy performance, Fault detection and diagnosis (FDD), clustering, symbolic aggregate approximation (SAX), Bag of words representation (BoWR), hierarchical clustering, Dynamic time warping (DTW)
Usman Habib, Gerhard Zucker, "Finding the Different Patterns in Buildings Data Using Bag of Words Representation with Clustering", 2015 13th International Conference on Frontiers of Information Technology (FIT), vol. 00, no. , pp. 303-308, 2015, doi:10.1109/FIT.2015.60
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