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dc.contributor.authorCorchado Rodríguez, Juan Manuel 
dc.contributor.authorLees, Brian
dc.contributor.authorAiken, Jim
dc.date.accessioned2017-09-05T11:02:33Z
dc.date.available2017-09-05T11:02:33Z
dc.date.issued2001
dc.identifier.citationInt. J. Comp. Intel. Appl.. Volumen 01 (01), pp. 35-52. World Scientific Pub Co Pte Lt.
dc.identifier.issn1469-0268 (Print) / 1757-5885 (Online)
dc.identifier.urihttp://hdl.handle.net/10366/134476
dc.description.abstractAn instance-based problem solving model is presented in which the aim is to forecast, in real time, the physical parameter values of a complex and dynamic environment: the ocean. The situations in which the rules that determine a system are unknown, the prediction of the parameter values that determine the characteristic behaviour of the system can be a problematic task. In such a situation it has been found that an instance-based reasoning system can provide a more effective means of performing such predictions than other connectionist or symbolic techniques. The instance-based reasoning system incorporates a radial basis function artificial neural network for the instance adaptation. The results obtained from experiments, in which the system operated in real time in the oceanographic environment, are presented.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherWorld Scientific Pub Co Pte Lt
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectComputer Science
dc.titleHybrid Instance-bsed system for predicting ocean temperatures
dc.typeinfo:eu-repo/semantics/article
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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