Abstract
The paper presents some new methods of knowledge acquisition and processing with regard to neuro-fuzzy systems. Various connectionist architectures that reflect fuzzy IF-THEN rules are considered. The so-called flexible neuro-fuzzy systems are described, as well as relational systems and probabilistic neural networks. Other connectionist systems, such hierarchical neuro-fuzzy systems, type 2 systems, and hybrid rough-neuro-fuzzy systems are mentioned. Finally, the perception-based approach, which refers to computing with words and perceptions, is briefly outlined. Within this framework, a multi-stage classification algorithm and a multi-expert classifier are proposed.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
