Zobrazeno 1 - 4
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pro vyhledávání: '"M. Aranzazu Simon"'
Publikováno v:
Current Topics in Artificial Intelligence ISBN: 9783642142635
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Due to the high number of gene expressions contained on microarray data, feature extraction techniques are usually applied before inducing classifiers. A common criterion to decide on the number of selected genes is minimizing the classifier error. H
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a52f9e99ad1dd5cbd6cf043b485e1e2b
https://doi.org/10.1007/978-3-642-14264-2_12
https://doi.org/10.1007/978-3-642-14264-2_12
Autor:
Juan José Rodríguez Diez, Anibal Bregon, M. Aranzazu Simon, Carlos J. Alonso-González, Oscar J. Prieto, Isaac Moro, Belarmino Pulido
Publikováno v:
Scopus-Elsevier
Consistency-based diagnosis automatically provides fault detection and localization capabilities, using just models for correct behavior. However, it may exhibit a lack of discrimination power. Knowledge about fault modes can be added to tackle the p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d5644142860917d249af92b5605ec9eb
https://doi.org/10.23919/ecc.2007.7068686
https://doi.org/10.23919/ecc.2007.7068686
Autor:
Anibal Bregon, Carlos J. Alonso, Isaac Moro, Juan J. Rodríguez, Belarmino Pulido, M. Aranzazu Simon
Publikováno v:
Current Topics in Artificial Intelligence ISBN: 9783540459149
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Scopus-Elsevier
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In this paper we introduce a system for early classification of several fault modes in a continuous process. Early fault classification is basic in supervision and diagnosis systems, since a fault could arise at any time, and the system must identify
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e55b39c3eeae34bc2240f18068ce5cff
https://doi.org/10.1007/11881216_23
https://doi.org/10.1007/11881216_23
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