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Contemporary training methodologies based on evolutionary artificial neural networks with product and sigmoid neurons for classification
dc.creator | Tallón Ballesteros, Antonio Javier | es |
dc.date.accessioned | 2024-02-12T11:58:39Z | |
dc.date.available | 2024-02-12T11:58:39Z | |
dc.date.issued | 2016-04 | |
dc.identifier.citation | Tallón Ballesteros, A.J. (2016). Contemporary training methodologies based on evolutionary artificial neural networks with product and sigmoid neurons for classification. AI Communications,, 29 (2), 469-471. https://doi.org/10.3233/AIC-150681. | |
dc.identifier.issn | 1875-8452 | es |
dc.identifier.uri | https://hdl.handle.net/11441/155157 | |
dc.description.abstract | This thesis introduces three contributions to train feed-forward neural network models based on evolutionary computation for a classification task. The new methodologies have been evaluated in three-layered neural models, including one input, one hidden and one output layer. Particularly, two kind of neurons such as product and sigmoidal units have been considered in an independent fashion for the hidden layer. Experiments have been carried out in a good number of problems, including three complex real-world problems, and the overall assessment of the new algorithms is very outstanding. Statistical tests shed light on that significant improvements were achieved. The applicability of the proposals is wide in the sense that can be extended to any kind of hidden neuron, either to other kind of problems like regression or even optimization with special emphasis in the two first approaches. | es |
dc.format | application/pdf | es |
dc.format.extent | 2 p. | es |
dc.language.iso | eng | es |
dc.publisher | IOP Press | es |
dc.relation.ispartof | AI Communications,, 29 (2), 469-471. | |
dc.subject | Artificial neural networks | es |
dc.subject | evolutionary algorithm | es |
dc.subject | classification | es |
dc.subject | Product units | es |
dc.subject | sigmoid unit | es |
dc.subject | feature selection | es |
dc.title | Contemporary training methodologies based on evolutionary artificial neural networks with product and sigmoid neurons for classification | es |
dc.type | info:eu-repo/semantics/article | es |
dc.type.version | info:eu-repo/semantics/acceptedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos | es |
dc.relation.projectID | TIN2007-68084-C02-02 | es |
dc.relation.projectID | TIN2008-06681-C06-03 | es |
dc.relation.projectID | TIN2011-28956-C02-02 | es |
dc.identifier.doi | 10.3233/AIC-150681 | es |
dc.journaltitle | AI Communications, | es |
dc.publication.volumen | 29 | es |
dc.publication.issue | 2 | es |
dc.publication.initialPage | 469 | es |
dc.publication.endPage | 471 | es |
dc.contributor.funder | Ministerio de Ciencia y Tecnología (MCYT). España | es |
dc.contributor.funder | European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER) | es |
dc.contributor.funder | Junta de Andalucía | es |
Ficheros | Tamaño | Formato | Ver | Descripción |
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