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dc.contributor.author | Corchado Rodríguez, Juan Manuel | |
dc.contributor.author | Lees, Brian | |
dc.date.accessioned | 2017-09-05T11:02:32Z | |
dc.date.available | 2017-09-05T11:02:32Z | |
dc.date.issued | 2001 | |
dc.identifier.citation | Applied Artificial Intelligence. Volumen 15 (2), pp. 105-127. Informa UK Limited. | |
dc.identifier.issn | 0883-9514 (Print) / 1087-6545 (Online) | |
dc.identifier.uri | http://hdl.handle.net/10366/134474 | |
dc.description.abstract | An investigation is described into the application of artificial intelligence to forecasting in the domain of oceanography. A hybrid approach to forecasting the thermal structure of the water ahead of a moving vessel is presented which combines the ability of a case-based reasoning system for identifying previously encountered similar situations and the generalizing ability of an artificial neural network to guide the adaptation stage of the case-based reasoning mechanism. The system has been successfully tested in real time in the Atlantic Ocean; the results obtained are presented and compared with those derived from other forecasting methods. | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dc.publisher | Informa UK Limited | |
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 | A hybrid case-based model for forecasting | |
dc.type | info:eu-repo/semantics/article | |
dc.rights.accessRights | info:eu-repo/semantics/openAccess |
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