A new method for fuzzy interpolative reasoning in sparse fuzzy rule-based systems

Author

Yu-Chuan Chang ; Shyi-Ming Chen

Author_Institution

Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan

fYear

2012

fDate

16-18 Nov. 2012

Firstpage

400

Lastpage

405

Abstract

In this paper, we present a new fuzzy interpolative reasoning method for sparse fuzzy rule-based systems. The proposed method not only can deal with multiple fuzzy rules interpolation based on polygonal membership functions, but also can overcome the drawbacks of the existing methods. It also guarantees the convexity of fuzzy interpolative reasoning results. The experimental result shows that the proposed method can generate more reasonable fuzzy interpolative reasoning results than the existing methods for sparse fuzzy rule-based systems.

Keywords

fuzzy reasoning; fuzzy set theory; interpolation; knowledge based systems; fuzzy interpolative reasoning method; multiple fuzzy rules interpolation; polygonal membership functions; sparse fuzzy rule-based systems; Argon; Bismuth; Cognition; Educational institutions; Fuzzy sets; Interpolation; Vectors; Fuzzy interpolative reasoning; multiple fuzzy rules interpolation; polygonal membership functions; sparse fuzzy rule-based systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Theory and it's Applications (iFUZZY), 2012 International Conference on

Conference_Location

Taichung

Print_ISBN

978-1-4673-2057-3

Type

conf

DOI

10.1109/iFUZZY.2012.6409739

Filename

6409739