Title :
Performance improvement of the fuzzy rule interpolation method LESFRI
Author_Institution :
Dept. of Inf. Technol., Kecskemet Coll., Kecskemét, Hungary
Abstract :
Fuzzy rule interpolation (FRI) methods could be advantageous tools for fuzzy inference owing to their capability to reason in sparse rule bases as well. The fuzzy rule interpolation by the least squares method (LESFRI) like most of the available techniques is designed so that it can be implemented easily only by using the traditional structure based fuzzy inference system (FIS) representation also applied by the FRI Matlab ToolBox. In this paper, we propose a new vector based internal FIS representation (VFIS) and an enhanced version of LESFRI (VLESFRI) designed for the use of VFIS. The performance improvement achievable by the application of VLESFRI is proved by several test results.
Keywords :
fuzzy reasoning; fuzzy set theory; interpolation; knowledge based systems; least squares approximations; FRI Matlab ToolBox; VLESFRI; fuzzy rule interpolation method; least squares method; performance improvement; structure based fuzzy inference system representation; vector based internal FIS representation; Arrays; Fuzzy sets; Fuzzy systems; Interpolation; Upper bound; Vectors;
Conference_Titel :
Computational Intelligence and Informatics (CINTI), 2011 IEEE 12th International Symposium on
Conference_Location :
Budapest
Print_ISBN :
978-1-4577-0044-6
DOI :
10.1109/CINTI.2011.6108512