2013 Fiscal Year Final Research Report
Classification for multivariate and multidimensional spatio-temporal data based on echelon hierarchical structure and its application
| Project/Area Number |
23500352
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Statistical science
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| Research Institution | Okayama University |
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Principal Investigator |
KURIHARA Koji 岡山大学, その他の研究科, 教授 (20170087)
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| Project Period (FY) |
2011 – 2013
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| Keywords | ホットスポット / 時空間情報 / エシェロン解析 |
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| Research Abstract |
In this research, we explore the classification for multivariate and multidimensional spatio-temporal data based on echelon structure. We newly develop the technique to detect the candidate of hotspot based on echelon peaks and foundations. We also develop the algorithm to identify the zone and the patch based on practical definition for the relation of peaks and foundations. In addition, we demonstrate some illustrations to detect the zones and the patch for spatio-temporal data.
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[Journal Article] Discriminant Analysis of Native Thoracic Aortic Curvature : Risk Prediction for Endoleak Formation After Thoracic Endovascular Aortic Repair2011
Author(s)
Nakatamari, H., Ueda, T., Ishioka F., Raman, B., Kurihara, K., Rubin, G., Ito, H. and Sze, D
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Journal Title
Journal of Vascular and Interventional Radiology
Volume: 22(7)
Pages: 974-979
DOI
Peer Reviewed
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