Identifying fuzzy systems from numerical data with Xfuzzy
Iluminada Baturone, Francisco J. Moreno-Velo, Andrés Gersnoviez · European Society for Fuzzy Logic and Technology Conference · 2005
Extracting fuzzy rule bases from numerical data draws a great interest nowadays. Several algorithms based on grid partitions or clustering have been reported in the literature for this purpose, and several CAD tools have been developed to implement one or other type of techniques. This paper presents the CAD tool xfdm that allows applying both types of techniques. In particular, it permits to select among four types of grid-based techniques and five types of clustering algorithms. Advantages of this tool is that it is integrated into the Xfuzzy 3 environment, and, hence, the identified rule base can be described, verified, tuned, simplified, and synthesized with the corresponding tools of Xfuzzy 3.