Learning of Interval and General Type-2 Fuzzy Logic Systems using Simulated Annealing: Theory and Practice
| dc.cclicence | CC-BY-NC | en |
| dc.contributor.author | Almaraashi, M. | en |
| dc.contributor.author | John, Robert, 1955- | en |
| dc.contributor.author | Hopgood, A. | en |
| dc.contributor.author | Ahmadi, S. | en |
| dc.date.acceptance | 2016-03-28 | en |
| dc.date.accessioned | 2016-07-04T15:30:46Z | |
| dc.date.available | 2016-07-04T15:30:46Z | |
| dc.date.issued | 2016-04-01 | |
| dc.description.abstract | This paper reports the use of simulated annealing to design more efficient fuzzy logic systems to model problems with associated uncertainties. Simulated annealing is used within this work as a method for learning the best configurations of interval and general type-2 fuzzy logic systems to maximize their modeling ability. The combination of simulated annealing with these models is presented in the modeling of four benchmark problems including real-world problems. The type-2 fuzzy logic system models are compared in their ability to model uncertainties associated with these problems. Issues related to this combination between simulated annealing and fuzzy logic systems, including type-2 fuzzy logic systems, are discussed. The results demonstrate that learning the third dimension in type-2 fuzzy sets with a deterministic defuzzifier can add more capability to modeling than interval type-2 fuzzy logic systems. This finding can be seen as an important advance in type-2 fuzzy logic systems research and should increase the level of interest in the modeling applications of general type-2 fuzzy logic systems, despite their greater computational load. | en |
| dc.funder | N/A | en |
| dc.identifier.citation | Almaraashi, M. John, R., Hopgood, A. and Ahmadi, S. (2016) Learning of interval and general type-2 fuzzy logic systems using simulated annealing: Theory and practice. Information Sciences, 360, pp. 21-42 | en |
| dc.identifier.doi | https://doi.org/10.1016/j.ins.2016.03.047 | |
| dc.identifier.issn | 0020-0255 | |
| dc.identifier.uri | http://hdl.handle.net/2086/12236 | |
| dc.language.iso | en | en |
| dc.peerreviewed | Yes | en |
| dc.projectid | N/A | en |
| dc.publisher | Elsevier | en |
| dc.researchgroup | Centre for Computational Intelligence | en |
| dc.subject | simulated annealing | en |
| dc.subject | interval type-2 fuzzy logic systems | en |
| dc.subject | general type-2 fuzzy logic systems | en |
| dc.subject | learning | en |
| dc.title | Learning of Interval and General Type-2 Fuzzy Logic Systems using Simulated Annealing: Theory and Practice | en |
| dc.type | Article | en |