Scale and move transformation-based fuzzy rule interpolation with interval type-2 fuzzy sets

Chengyuan Chen, Chai Quek, Qiang Shen

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

14 Citations (SciVal)


Fuzzy rule interpolation (FRI) is an important technique for performing inference with sparse rule bases. Even when a given observation has no overlap with the antecedent values of any existing rules, FRI may still derive a conclusion. In particular, the scale and move transformation-based approach can handle interpolation and extrapolation with multiple multi-antecedent rules. However, the difficulty in defining the required precise-valued membership functions significantly restricts the application of FRI. Type-2 fuzzy sets help to alleviate such limitations because their membership functions are themselves fuzzy. This paper extends the existing transformation-based approach of FRI by using interval type-2 fuzzy sets. The proposed approach not only facilitates the definition of representative values of interval type-2 fuzzy sets, but also modifies the underlying FRI technique to ensure intuitive interpolated conclusions. The experimentation demonstrates that the proposed approach can deal with uncertainty in FRI in a more flexible way, extending the potential of conventional FRI techniques.
Original languageEnglish
Title of host publicationProceedings of the 22nd International Conference on Fuzzy Systems
PublisherIEEE Press
Number of pages8
ISBN (Print)978-1-4799-0020-6
Publication statusPublished - 2013
EventFuzzy Systems - Hyderabad, Hyderabad, India
Duration: 07 Jul 201310 Jul 2013
Conference number: 22


ConferenceFuzzy Systems
Abbreviated titleFUZZ-IEEE-2013
Period07 Jul 201310 Jul 2013


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