Scale and move transformation-based fuzzy interpolative reasoning: A revisit

Zhiheng Huang, Qiang Shen

Research output: Contribution to conferencePaper

12 Citations (SciVal)
28 Downloads (Pure)


This paper generalises the previously proposed interpolative reasoning method [5] to cover interpolations involving complex polygon, Gaussian or other bell-shaped fuzzy membership functions. This can be achieved by the generality of the proposed scale and move transformations. The method works by first constructing a new inference rule via manipulating two given adjacent rules, and then by using scale and move transformations to convert the intermediate inference results into the final derived conclusions. This generalised method has two advantages thanks to the elegantly proposed transformations: 1) It can easily handle interpolation of multiple antecedent variables with simple computation; and 2) It guarantees the uniqueness as well as normality and convexity of the resulting interpolated fuzzy sets. Numerical examples are provided to demonstrate the use of this method.
Original languageEnglish
Number of pages6
Publication statusPublished - 2004


Dive into the research topics of 'Scale and move transformation-based fuzzy interpolative reasoning: A revisit'. Together they form a unique fingerprint.

Cite this