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.
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Subject (DDC): | 004 Computer Science |
Link to License: | In Copyright |
Bibliography of Konstanz: | Yes |
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
@inproceedings{Hao2009-10Poste-19202, title={Poster : Visual Prediction of Time Series}, year={2009}, doi={10.1109/VAST.2009.5333420}, isbn={978-1-4244-5283-5}, publisher={IEEE}, booktitle={2009 IEEE Symposium on Visual Analytics Science and Technology}, pages={229--230}, author={Hao, Ming and Janetzko, Halldor and Sharma, Ratnesh and Dayal, Umeshwar and Keim, Daniel and Castellanos, Malu} }
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Hao_Visual prediction.pdf | 714 |