Nascimento, S. and Mirkin, Boris (2017) Applying anomalous cluster approach to spatial clustering. In: Kreinovich, V. (ed.) Uncertainty Modeling. Studies in Computational Intelligence 683. Springer, pp. 147-157. ISBN 9783319510514.
Abstract
The concept of anomalous clustering applies to finding individual clusters on a digital geography map supplied with a single feature such as brightness or temperature. An algorithm derived within the individual anomalous cluster framework extends the so-called region growing algorithms. Yet our approach differs in that the algorithm parameter values are not expert-driven but rather derived from the anomalous clustering model. This novel framework successfully applies to the issue of automatically delineating coastal upwelling from Sea Surface Temperature (SST) maps, a natural phenomenon seasonally occurring in coastal waters.
Metadata
| Item Type: | Book Section |
|---|---|
| Additional Information: | Dedicated to Professor Boris Kovalerchuk on his Anniversary. Series ISSN: 1860-949X |
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
| Depositing User: | Administrator |
| Date Deposited: | 12 Jun 2017 06:59 |
| Last Modified: | 09 Aug 2023 12:41 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/18853 |
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