Kaolin quality determination through an algorithm based on non-parametric fuzzy logic
In this article we describe a new fuzzy supervised classification method that is a modification of the fuzzy pattern-matching multidensity classifier. The latter has been demonstrated to be one of the most effective classifiers for non-convex classes. Implementing a non- parametric density estimator...
- Autores:
-
Ordóñez, Celestino
Saavedra, Angeles
Araújo, María
Giráldez, Eduardo
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2012
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/40595
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/40595
http://bdigital.unal.edu.co/30692/
- Palabra clave:
- classification
fuzzy set
non-parametric fuzzy logic
kaolin quality
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| Summary: | In this article we describe a new fuzzy supervised classification method that is a modification of the fuzzy pattern-matching multidensity classifier. The latter has been demonstrated to be one of the most effective classifiers for non-convex classes. Implementing a non- parametric density estimator in one stage of the parametric method, we developed a fuzzy non-parametric classifier that manages to avoid some of the problems associated with the parametric method. The method was applied to a mineralogy problem consistingof classifying kaolin samples according to different ceramic quality levels. Our results produced error percentages that were lower than those for the parametric method. |
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