Poster : Visual Prediction of Time Series

Type of Publication: Contribution to a conference collection
URI (citable link): http://nbn-resolving.de/urn:nbn:de:bsz:352-192027
Author: Hao, Ming; Janetzko, Halldor; Sharma, Ratnesh; Dayal, Umeshwar; Keim, Daniel; Castellanos, Malu
Year of publication: 2009
Conference: 2009 IEEE Symposium on Visual Analytics Science and Technology, Oct 12, 2009 - Oct 13, 2009, Atlantic City, NJ, USA
Published in: 2009 IEEE Symposium on Visual Analytics Science and Technology. - IEEE, 2009. - pp. 229-230. - ISBN 978-1-4244-5283-5
DOI (citable link): https://dx.doi.org/10.1109/VAST.2009.5333420
Summary:
Many well-known time series prediction methods have been used daily by analysts making decisions. To reach a good prediction, we introduce several new visual analysis techniques of smoothing, multi-scaling, and weighted average with the involvement of human expert knowledge. We combine them into a well-fitted method to perform prediction. We have applied this approach to predict resource consumption in data center for next day planning.
Subject (DDC): 004 Computer Science
Link to License: In Copyright
Bibliography of Konstanz: Yes

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HAO, Ming, Halldor JANETZKO, Ratnesh SHARMA, Umeshwar DAYAL, Daniel KEIM, Malu CASTELLANOS, 2009. Poster : Visual Prediction of Time Series. 2009 IEEE Symposium on Visual Analytics Science and Technology. Atlantic City, NJ, USA, Oct 12, 2009 - Oct 13, 2009. In: 2009 IEEE Symposium on Visual Analytics Science and Technology. IEEE, pp. 229-230. ISBN 978-1-4244-5283-5. Available under: doi: 10.1109/VAST.2009.5333420

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