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Design and simulate fuzzy logic systems using Type-1 and Interval Type-2 Fuzzy Logic. This toolkit includes with graphical user interface (GUI) and an adaptive neuro- fuzzy inference system (ANFIS). This toolkit is a continuation from the previous package ('FuzzyToolkitUoN'). Produced by the Intelligent Modelling & Analysis Group (IMA) and Lab for UnCertainty In Data and decision making (LUCID), University of Nottingham. A big thank you to the many people who have contributed to the development/evaluation of the toolbox. Please cite the toolbox and the corresponding paper <doi:10.1109/FUZZ48607.2020.9177780> when using it. More related papers can be found in the NEWS.
Version: | 2.3.2 |
Depends: | R (≥ 3.6.0) |
Imports: | splines, shiny, plyr, grid, stats, graphics |
Published: | 2021-05-19 |
DOI: | 10.32614/CRAN.package.FuzzyR |
Author: | Chao Chen [aut, cre], Jon Garibaldi [aut], Tajul Razak [aut] |
Maintainer: | Chao Chen <fuzzyr at cs.nott.ac.uk> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | https://www.lucidresearch.org/ |
NeedsCompilation: | no |
Materials: | NEWS |
CRAN checks: | FuzzyR results |
Reference manual: | FuzzyR.pdf |
Package source: | FuzzyR_2.3.2.tar.gz |
Windows binaries: | r-devel: FuzzyR_2.3.2.zip, r-release: FuzzyR_2.3.2.zip, r-oldrel: FuzzyR_2.3.2.zip |
macOS binaries: | r-release (arm64): FuzzyR_2.3.2.tgz, r-oldrel (arm64): FuzzyR_2.3.2.tgz, r-release (x86_64): FuzzyR_2.3.2.tgz, r-oldrel (x86_64): FuzzyR_2.3.2.tgz |
Old sources: | FuzzyR archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.