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dc.contributor.author Chen, Chengyuan
dc.contributor.author Shen, Qiang
dc.date.accessioned 2017-08-21T19:18:30Z
dc.date.available 2017-08-21T19:18:30Z
dc.date.issued 2017-08-15
dc.identifier.citation Chen , C & Shen , Q 2017 , ' Transformation-Based Fuzzy Rule Interpolation Using Interval Type-2 Fuzzy Sets ' Algorithms , vol. 10 , no. 3 , 91 . https://doi.org/10.3390/a10030091 en
dc.identifier.issn 1999-4893
dc.identifier.other PURE: 18865749
dc.identifier.other PURE UUID: 53a77513-2ba5-4cb2-b29a-e3b90983539d
dc.identifier.other Scopus: 85029755098
dc.identifier.other handle.net: 2160/45496
dc.identifier.uri http://hdl.handle.net/2160/45496
dc.description.abstract In support of reasoning with sparse rule bases, fuzzy rule interpolation (FRI) offers a helpful inference mechanism for deriving an approximate conclusion when a given observation has no overlap with any rule in the existing rule base. One of the recent and popular FRI approaches is the scale and move transformation-based rule interpolation, known as T-FRI in the literature. It supports both interpolation and extrapolation with multiple multi-antecedent rules. However, the difficult problem of defining the precise-valued membership functions required in the representation of fuzzy rules, or of the observations, restricts its applications. Fortunately, this problem can be alleviated through the use of type-2 fuzzy sets, owing to the fact that the membership functions of such fuzzy sets are themselves fuzzy, providing a more flexible means of modelling. This paper therefore, extends the existing T-FRI approach using interval type-2 fuzzy sets, which covers the original T-FRI as its specific instance. The effectiveness of this extension is demonstrated by experimental investigations and, also, by a practical application in comparison to the state-of-the-art alternative approach developed using rough-fuzzy sets en
dc.language.iso eng
dc.relation.ispartof Algorithms en
dc.rights en
dc.subject fuzzy rule interpolation en
dc.subject interval type-2 fuzzy sets en
dc.subject transformation-based interpolation en
dc.title Transformation-Based Fuzzy Rule Interpolation Using Interval Type-2 Fuzzy Sets en
dc.type /dk/atira/pure/researchoutput/researchoutputtypes/contributiontojournal/article en
dc.description.version publishersversion en
dc.identifier.doi https://doi.org/10.3390/a10030091
dc.contributor.institution IMPACS en
dc.description.status Peer reviewed en


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