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The usefulness of artificial intelligence techniques to assess subjective quality of products in the food industry

dc.contributor.authorGoyache, F.
dc.contributor.authorBahamonde Rionda, Antonio 
dc.contributor.authorAlonso González, Jaime 
dc.contributor.authorLópez García, José Secundino 
dc.contributor.authorCoz Velasco, Juan José del 
dc.contributor.authorQuevedo Pérez, José Ramón 
dc.contributor.authorRanilla Pastor, José 
dc.contributor.authorLuaces Rodríguez, Óscar 
dc.contributor.authorÁlvarez, I.
dc.contributor.authorRoyo Martín, Luis J.
dc.contributor.authorDíez Peláez, Jorge 
dc.date.accessioned2020-01-16T10:52:07Z
dc.date.available2020-01-16T10:52:07Z
dc.date.issued2001
dc.identifier.citationTrends in Food Science & Technology, 12 (10), p. 370-381 (2001); doi:10.1016/S0924-2244(02)00010-9
dc.identifier.issn0924-2244
dc.identifier.urihttp://hdl.handle.net/10651/53592
dc.description.abstractIn this paper we advocate the application of Artificial Intelligence techniques to quality assessment of food products. Machine Learning algorithms can help us to: (a) extract operative human knowledge from a set of examples; (b) conclude interpretable rules for classifying samples regardless of the non-linearity of the human behaviour or process; and (c) help us to ascertain the degree of influence of each objective attribute of the assessed food on the final decision of an expert. We illustrate these topics with an example of how it is possible to clone the behaviour of bovine carcass classifiers, leading to possible further industrial applicationsspa
dc.description.sponsorshipThis paper was partially funded by a grant from CICYT-FEDER, No. 1FD97–1633 and by DGES PB98–1556. The authors would like to thank Marı́a Fernández, Jesús Fernández Tejón and Fernando Ureña from Empresa Asturiana de Servicios Agrarios (EASA) for their invaluable help and comments, and the authors of Cubist and M5 for allowing us to use their softwarespa
dc.format.extentp. 370-381spa
dc.language.isoengspa
dc.publisherElsevierspa
dc.relation.ispartofTrends in Food Science & Technology, 12 (10)spa
dc.rights© 2002 Elsevier Science Ltd.
dc.rightsCC Reconocimiento - No Comercial - Sin Obra Derivada 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleThe usefulness of artificial intelligence techniques to assess subjective quality of products in the food industryspa
dc.typejournal articlespa
dc.identifier.doi10.1016/S0924-2244(02)00010-9
dc.relation.projectIDCICYT-FEDER/1FD97–1633
dc.relation.publisherversionhttps://doi.org/10.1016/S0924-2244(02)00010-9spa
dc.rights.accessRightsopen access
dc.type.hasVersionAM


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© 2002 Elsevier Science Ltd.
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