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Evolutionary cellular configurations for designing feed-forward neural networks architectures

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Computación Evolutiva y Redes Neuronales (EVANNAI)es
dc.contributor.authorGutiérrez Sánchez, Germán
dc.contributor.authorIsasi, Pedro
dc.contributor.authorMolina López, José Manuel
dc.contributor.authorSanchis de Miguel, María Araceli
dc.contributor.authorGalván, Inés M.
dc.date.accessioned2009-04-17T12:42:59Z
dc.date.available2009-04-17T12:42:59Z
dc.date.issued2001
dc.descriptionProceeding of: 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13–15, 2001
dc.description.abstractIn the recent years, the interest to develop automatic methods to determine appropriate architectures of feed-forward neural networks has increased. Most of the methods are based on evolutionary computation paradigms. Some of the designed methods are based on direct representations of the parameters of the network. These representations do not allow scalability, so to represent large architectures, very large structures are required. An alternative more interesting are the indirect schemes. They codify a compact representation of the neural network. In this work, an indirect constructive encoding scheme is presented. This scheme is based on cellular automata representations in order to increase the scalability of the method.
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationConnectionist models of neurons, learning processes, and Artificial Intelligence. Berlin: Springer, 2001. p. 514-521 (Lecture Notes in Computer Science; 2084)
dc.identifier.doi10.1007/3-540-45720-8_61
dc.identifier.isbn978-3-540-42235-8
dc.identifier.issn1611-3349 (Online)
dc.identifier.publicationfirstpage514
dc.identifier.publicationlastpage521
dc.identifier.publicationtitleConnectionist models of neurons, learning processes, and Artificial Intelligence
dc.identifier.urihttps://hdl.handle.net/10016/4003
dc.language.isoeng
dc.publisherSpringer
dc.relation.eventdateJune 13–15, 2001
dc.relation.eventnumber6
dc.relation.eventplaceGranada (Spain)
dc.relation.eventtitleInternational Work-Conference on Artificial and Natural Neural Networks, IWANN 2001
dc.relation.ispartofseriesLecture Notes in Computer Science
dc.relation.ispartofseriesVolume 2084/2001
dc.relation.publisherversionhttp://dx.doi.org/10.1007/3-540-45720-8_61
dc.rights© Springer
dc.rights.accessRightsopen access
dc.subject.ecienciaInformática
dc.titleEvolutionary cellular configurations for designing feed-forward neural networks architectures
dc.typeconference paper*
dspace.entity.typePublication
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