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dc.contributor.authorMata Conde, Aitor
dc.contributor.authorMuñoz Vicente, María Dolores 
dc.contributor.authorCorchado Rodríguez, Emilio Santiago 
dc.contributor.authorCorchado Rodríguez, Juan Manuel 
dc.date.accessioned2017-09-05T11:01:44Z
dc.date.available2017-09-05T11:01:44Z
dc.date.issued2011
dc.identifier.citationJournal of Mathematical Imaging and Vision. Volumen 42 (2-3), pp. 212-224. Springer Science + Business Media.
dc.identifier.issn0924-9907(Print)/ 1573-7683(Online)
dc.identifier.urihttp://dx.doi.org/10.1007/s10851-011-0315-x
dc.identifier.urihttp://hdl.handle.net/10366/134384
dc.description.abstractA novel hybrid forecasting Case-Based Reasoning (CBR) system is presented in this interdisciplinary study in which an isotropic buffer operator is applied for case-based creation. Commonly used as an image analysis technique by commercial Geographic Information Systems (GIS), the buffer operator in this particular system calculates the area of an oil slick for prediction and visualization tasks. The use of the buffer operator improves the quality of the data used by the system and in consequence the quality of the results obtained. The system generates predictions by using historical data on oil-slick formation following a spill.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherSpringer Science + Business Media
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectComputer Science
dc.titleIsotropic Image Analysis for Improving CBR Forecasting
dc.typeinfo:eu-repo/semantics/article
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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Attribution-NonCommercial-NoDerivs 3.0 Unported
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Unported