Abstract-- The concept of an M-approximative system is introduced. Basic properties of the category of M-approximative systems and in a natural way defined morphisms between them a...
The use of bagging is explored to create an ensemble of fuzzy classifiers. The learning algorithm used was ANFIS (Adaptive Neuro-Fuzzy Inference Systems). We compare results from b...
Juana Canul-Reich, Larry Shoemaker, Lawrence O. Ha...
Following Breiman’s methodology, we propose a multi-classifier based on a “forest” of randomly generated fuzzy decision trees, i.e., a Fuzzy Random Forest. This approach co...
This article deals with the recognition of recurring multivariate time series patterns modelled sample-point-wise by parametric fuzzy sets. An efficient classification-based approa...
In spite of its successes as a tool in the field of engineering, fuzzy set theory has yet to achieve the universal footing that probability theory has across the various fields ...