Type-2 fuzzy sets: geometric defuzzification and type-reduction
| dc.contributor.author | Coupland, Simon | en |
| dc.date.accessioned | 2008-11-24T13:24:16Z | |
| dc.date.available | 2008-11-24T13:24:16Z | |
| dc.date.issued | 2007-02-01 | en |
| dc.description | This paper presents the geometric defuzzifier for general type-2 fuzzy sets. This novel method has the potential to transform the fuzzy control paradigm. General type-2 fuzzy logic is better able to model noise and uncertainty but suffers from the massive computational cost of defuzzification. This paper uses geometry to eliminate this problem, paving the way for general type-2 fuzzy control. This paper was shortlisted for the best paper award at this prestigious international conference. | en |
| dc.identifier.citation | Coupland, S. (2007) Type-2 fuzzy sets: geometric defuzzification and type-reduction. Proceedings of IEEE Symposium on Foundations of Computational Intelligence, pp. 622-629. | |
| dc.identifier.doi | https://doi.org/10.1109/foci.2007.371537 | |
| dc.identifier.isbn | 1424407036 | |
| dc.identifier.uri | http://hdl.handle.net/2086/190 | |
| dc.language.iso | en | en |
| dc.researchgroup | Centre for Computational Intelligence | |
| dc.researchinstitute | Institute of Artificial Intelligence (IAI) | en |
| dc.subject | RAE 2008 | |
| dc.subject | UoA 23 Computer Science and Informatics | |
| dc.subject | geometric defuzzifier | |
| dc.title | Type-2 fuzzy sets: geometric defuzzification and type-reduction | en |
| dc.type | Other | en |