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https://hdl.handle.net/1822/2222
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Campo DC | Valor | Idioma |
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dc.contributor.author | Rocha, Miguel | - |
dc.contributor.author | Cortez, Paulo | - |
dc.contributor.author | Neves, José | - |
dc.date.accessioned | 2005-06-15T19:59:26Z | - |
dc.date.available | 2005-06-15T19:59:26Z | - |
dc.date.issued | 2005-06-08 | - |
dc.identifier.citation | INTERNATIONAL WORK-CONFERENCE ON ARTIFICIAL NEURAL NETWORKS (IWANN), 8, Barcelona, 2005 - "Computational intelligence and bioinspired systems : proceedings". Heidelberg : Springer, 2005. ISBN 3-540-26208-3. p. 59-66. | eng |
dc.identifier.isbn | 3-540-26208-3 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | https://hdl.handle.net/1822/2222 | - |
dc.description.abstract | Artificial Neural Networks (ANNs) are important Data Mining (DM) techniques. Yet, the search for the optimal ANN is a challenging task: the architecture should learn the input-output mapping without overfitting the data and training algorithms tend to get trapped into local minima. Under this scenario, the use of Evolutionary Computation (EC) is a promising alternative for ANN design and training. Moreover, since EC methods keep a pool of solutions, an ensemble can be build by combining the best ANNs. This work presents a novel algorithm for the optimization of ANNs, using a direct representation, a structural mutation operator and Lamarckian evolution. Sixteen real-world classification/regression tasks were used to test this strategy with single and ensemble based versions. Competitive results were achieved when compared with a heuristic model selection and other DM algorithms. | eng |
dc.description.sponsorship | Universidade do Minho. Centro Algoritmi. | por |
dc.description.sponsorship | Fundação para a Ciência e a Tecnologia (FCT) - POSI/EIA/59899/2004. | por |
dc.language.iso | eng | eng |
dc.publisher | Springer | eng |
dc.rights | openAccess | eng |
dc.subject | Supervised learning | eng |
dc.subject | Multilayer perceptrons | eng |
dc.subject | Evolutionary algorithms | eng |
dc.subject | Ensembles | eng |
dc.title | Simultaneous evolution of neural network topologies and weights for classification and regression | eng |
dc.type | conferencePaper | eng |
dc.peerreviewed | yes | eng |
dc.relation.publisherversion | The original publication is available at http://www.springerlink.com | - |
oaire.citationStartPage | 59 | por |
oaire.citationEndPage | 66 | por |
oaire.citationVolume | 3512 | por |
dc.subject.wos | Science & Technology | por |
sdum.journal | Lecture Notes in Computer Science | por |
sdum.conferencePublication | COMPUTATIONAL INTELLIGENCE AND BIOINSPIRED SYSTEMS, PROCEEDINGS | por |
Aparece nas coleções: | DI/CCTC - Artigos (papers) DSI - Engenharia da Programação e dos Sistemas Informáticos |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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spr-59.pdf | 201,85 kB | Adobe PDF | Ver/Abrir |