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http://hdl.handle.net/1843/42873| Tipo: | Artigo de Evento |
| Título: | A bee-inspired multiobjective optimization clustering algorithm |
| Autor(es): | Dávila Patrícia Ferreira Cruz Alexandre Alberto Politi Danilo Cunha Leandro Nunes de Castro Renato Dourado Maia |
| Resumen: | Multiobjective clustering techniques have been used to simultaneously consider several complementary aspects of clustering quality. They optimize more than one cluster validity index simultaneously, leading to high-quality re-sults, and have emerged as attractive and robust alternatives for clustering problems. This paper proposes a bee-inspired multiobjective optimization algorithm to solve data clustering problems. The algorithm was run for different datasets and the results obtained showed high quality clusters and diversity of solutions, whilst a suitable number of clusters was automatically determined. |
| Asunto: | Algoritmos Cluster (Sistema de computador) |
| Idioma: | eng |
| País: | Brasil |
| Editor: | Universidade Federal de Minas Gerais |
| Sigla da Institución: | UFMG |
| Departamento: | ICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS |
| Tipo de acceso: | Acesso Restrito |
| Identificador DOI: | 10.2316/P.2016.841-035 |
| URI: | http://hdl.handle.net/1843/42873 |
| Fecha del documento: | ago-2016 |
| metadata.dc.url.externa: | https://www.actapress.com/Abstract.aspx?paperId=456259 |
| metadata.dc.relation.ispartof: | Modelling, Simulation and Identification - MSI 2016 |
| Aparece en las colecciones: | Artigo de Evento |
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