Towards Rule-ranking Based Fuzzy Rule Interpolation

Mou Zhou, Changjing Shang, Pu Zhang, Guobin Li, Shangzhu Jin, Jun Peng, Qiang Shen

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


Recently proposed methods of TSK inference extension (TSK+) and K closest rules based TSK (KCR) are able to potentially perform fuzzy rule-based inference with a sparse rule base, for regression problems. However, in certain real-world applications, observations may be rather far away from any rules that may be fired in order to implement the required regression and hence, these state-of-the-art techniques may not work satisfactorily. To investigate an alternative to address such practical problems, this paper presents a novel fuzzy rule interpolation (FRI) approach. It works based on integrating feature selection and feature aggregation to attain a rule-ranking list within the given sparse rule base. The process of acquiring an ordered rule list is accomplished offline, with an ordered rule base ready for use prior to the arrival of any observation online. It boosts the computational efficiency of closest rule selection during the FRI process. Initial experimental results demonstrate that the proposed approach is able to address the problems that TSK+ and KCR fail to do while having a similar time efficiency to them. Further, only two nearest rules to the observation are required to derive interpolated results, thereby significantly improving the automation level of the interpolative reasoning system.

Original languageEnglish
Title of host publicationIEEE CIS International Conference on Fuzzy Systems 2021, FUZZ 2021 - Proceedings
PublisherIEEE Press
ISBN (Electronic)9781665444071
Publication statusPublished - 11 Jul 2021
EventFuzzy Systems - Virtual, Online, Luxembourg
Duration: 11 Jul 202114 Jul 2021
Conference number: 30

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584


ConferenceFuzzy Systems
Abbreviated titleFUZZ-IEEE-2021
CityVirtual, Online
Period11 Jul 202114 Jul 2021


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