Title :
Flexible weighted neuro-fuzzy systems
Author :
Rutkowski, Leszek ; Cpalka, Krzysztof
Author_Institution :
Dept. of Comput. Eng., Tech. Univ. Czestochowa, Poland
Abstract :
In the paper we study new neuro-fuzzy systems. They are called the OR-type fuzzy inference systems (NFIS). Based on the input-output data we learn not only parameters of membership functions but also a type of the systems and aggregating parameters. We propose the weighted T-norm and S-norm to neuro-fuzzy inference systems. Our approach introduces more flexibility to the structure and learning of neuro-fuzzy systems.
Keywords :
fuzzy neural nets; inference mechanisms; I/O data; NFIS; OR-type fuzzy inference systems; flexible weighted neuro-fuzzy systems; input-output data; membership function parameters; weighted S-norm; weighted T-norm; Aggregates; Fuzzy logic; Fuzzy systems; Softening; Switches;
Conference_Titel :
Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
Print_ISBN :
981-04-7524-1
DOI :
10.1109/ICONIP.2002.1198995
