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dc.contributor.author | Mata Conde, Aitor | |
dc.contributor.author | Corchado Rodríguez, Emilio Santiago | |
dc.contributor.author | Baruque, Bruno | |
dc.date.accessioned | 2017-09-06T09:15:12Z | |
dc.date.available | 2017-09-06T09:15:12Z | |
dc.date.issued | 2009 | |
dc.identifier.citation | International Symposium on Distributed Computing and Artificial Intelligence 2008 (DCAI 2008) Advances in Soft Computing. Advances in Soft Computing. Volumen 50, pp. 658-662. | |
dc.identifier.isbn | 978-3-540-85862-1 (Print) / 978-3-540-85863-8 (Online) | |
dc.identifier.issn | 1615-3871 (Print) / 1860-0794 (Online) | |
dc.identifier.uri | http://hdl.handle.net/10366/134957 | |
dc.description.abstract | In this paper, a forecasting system is presented. It predicts the presence of oil slicks in a certain area of the open sea after an oil spill using Case-Based Reasoning methodology. CBR systems are designed to generate solutions to a certain problem by analysing historical data where previous solutions are stored. The system explained includes a novel network for data classification and retrieval. Such network works as a summarization algorithm for the results of an ensemble of Self-Organizing Maps. This algorithm, called Weighted Voting Superposition (WeVoS), is aimed to achieve the lowest topographic error in the map. The WeVoS-CBR system has been able to precisely predict the presence of oil slicks in the open sea areas of the north west of the Galician coast. | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dc.publisher | Springer Science + Business Media | |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Unported | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/3.0/ | |
dc.subject | Computer Science | |
dc.title | Solving the Oil Spill Problem Using a Combination of CBR and a Summarization of SOM Ensembles | |
dc.type | info:eu-repo/semantics/article | |
dc.rights.accessRights | info:eu-repo/semantics/openAccess |
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