Knowledge-leverage based TSK fuzzy system with improved knowledge transfer

Publication Type:
Conference Proceeding
IEEE International Conference on Fuzzy Systems, 2014, pp. 178 - 185
Issue Date:
Full metadata record
Files in This Item:
Filename Description Size
k.pdfPublished version3.02 MB
Adobe PDF
© 2014 IEEE. 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.
Please use this identifier to cite or link to this item: