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 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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| Main Authors: | , , , |
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| Format: | Digital revista |
| Language: | English |
| Published: |
Universidad Nacional de Colombia
2012
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| Online Access: | http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0012-73532012000100007 |
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