Abstract
In this study, the improved knowledge-leverage based TSK fuzzy system modeling method is proposed in order to overcome the weaknesses of the knowledge-leverage based TSK fuzzy system (TSK-FS) modeling method. In particular, two improved knowledge-leverage strategies have been introduced for the parameter learning of the antecedents and consequents of the TSK-FS constructed in the current scene by transfer learning from the reference scene, respectively. With the improved knowledge-leverage learning abilities, the proposed method has shown the more adaptive modeling effect compared with traditional TSK fuzzy modeling methods and some related methods on the synthetic and real world datasets.
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.
