Pulsar detection for wavelets soda and regularized fuzzy neural networks based on andneuron and robust activation function.

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dc.contributor.authorSouza, Paulo Vitor de Campos
dc.contributor.authorTorres, Luiz Carlos Bambirra
dc.contributor.authorGuimarães, Augusto Júnio
dc.contributor.authorAraújo, Vanessa Souza
dc.date.accessioned2022-09-15T20:32:55Z
dc.date.available2022-09-15T20:32:55Z
dc.date.issued2019pt_BR
dc.description.abstractThe use of intelligent models may be slow because of the number of samples involved in the problem. The identification of pulsars (stars that emit Earth-catchable signals) involves collecting thousands of signals by professionals of astronomy and their identification may be hampered by the nature of the problem, which requires many dimensions and samples to be analyzed. This paper proposes the use of hybrid models based on concepts of regularized fuzzy neural networks that use the representativeness of input data to define the groupings that make up the neurons of the initial layers of the model. The andneurons are used to aggregate the neurons of the first layer and can create fuzzy rules. The training uses fast extreme learning machine concepts to generate the weights of neurons that use robust activation functions to perform pattern classification. To solve large-scale problems involving the nature of pulsar detection problems, the model proposes a fast and highly accurate approach to address complex issues. In the execution of the tests with the proposed model, experiments were conducted explanation in two databases of pulsars, and the results prove the viability of the fast and interpretable approach in identifying such involved stars.pt_BR
dc.identifier.citationSOUZA, P. V. de C. et al. Pulsar detection for wavelets soda and regularized fuzzy neural networks based on andneuron and robust activation function. International Journal on Artificial Intelligence Tools, v. 28, n. 1, artigo 1950003, 2019. Disponível em: <https://www.worldscientific.com/doi/10.1142/S0218213019500039>. Acesso em: 29 abr. 2022.pt_BR
dc.identifier.doihttps://doi.org/10.1142/S0218213019500039pt_BR
dc.identifier.issn1793-6349
dc.identifier.urihttp://www.repositorio.ufop.br/jspui/handle/123456789/15308
dc.identifier.uri2https://www.worldscientific.com/doi/10.1142/S0218213019500039pt_BR
dc.language.isoen_USpt_BR
dc.rightsrestritopt_BR
dc.titlePulsar detection for wavelets soda and regularized fuzzy neural networks based on andneuron and robust activation function.pt_BR
dc.typeArtigo publicado em periodicopt_BR
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