Kaolin quality determination through an algorithm based on non-parametric fuzzy logic

Abstract

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.