Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11851/5615
Title: | Clustering Uncertain Interval Data Using a New Hausdorff-Based Metric | Authors: | Zarandi, Mohammad Hossein Fazel Avazbeigi, Milad Anssari, M. H. Türkşen, İsmail Burhan |
Keywords: | Clustering interval data Component Hausdorff distance Pattern recognition Uncertain interval data |
Source: | 2010 Annual North American Fuzzy Information Processing Society Conference, NAFIPS'2010, 12 July 2010 through 14 July 2010, Toronto, ON, 81691 | Abstract: | This paper presents a new index for measuring interval distances and its related metric. The proposed index and metric are both based on the Hausdorff distance which can be used for clustering uncertain interval data. Then using the new metric, a clustering method is introduced for clustering of intervals. Finally, some experiments are provided to validate the method. Results show that the method can identify appropriate clusters efficiently. © 2010 IEEE. | URI: | https://doi.org/10.1109/NAFIPS.2010.5548291 https://hdl.handle.net/20.500.11851/5615 |
ISBN: | 9781424478576 |
Appears in Collections: | Endüstri Mühendisliği Bölümü / Department of Industrial Engineering Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
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