{ "_id": "6a102017acfb0bcc41c8b6e6", "Package": "FuzzyR", "Type": "Package", "Title": "Fuzzy Logic Toolkit for R", "Version": "2.3.2", "Packaged": { "Date": "2026-05-14 06:24:37 UTC", "User": "root" }, "Authors@R": "c(\nperson(\"Chao\", \"Chen\", email = \"fuzzyr@cs.nott.ac.uk\", role = c(\"aut\", \"cre\")),\nperson(\"Jon\", \"Garibaldi\", role = \"aut\"),\nperson(\"Tajul\", \"Razak\", role = \"aut\"))", "Description": "Design and simulate fuzzy logic systems using Type-1 and\nInterval Type-2 Fuzzy Logic. This toolkit includes with\ngraphical user interface (GUI) and an adaptive neuro- fuzzy\ninference system (ANFIS). This toolkit is a continuation from\nthe previous package ('FuzzyToolkitUoN'). Produced by the\nIntelligent Modelling & Analysis Group (IMA) and Lab for\nUnCertainty In Data and decision making (LUCID), University of\nNottingham. A big thank you to the many people who have\ncontributed to the development/evaluation of the toolbox.\nPlease cite the toolbox and the corresponding paper\n when using it. More\nrelated papers can be found in the NEWS.", "License": "GPL (>= 2)", "URL": "https://www.lucidresearch.org/", "RoxygenNote": "7.1.1", "NeedsCompilation": "no", "Encoding": "UTF-8", "Author": "Chao Chen [aut, cre], Jon Garibaldi [aut], Tajul Razak [aut]", "Maintainer": "Chao Chen ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2021-05-19 08:00:05 UTC", "RemoteUrl": "https://github.com/cran/FuzzyR", "RemoteRef": "HEAD", "RemoteSha": "9cc8853d055c08356d073a3572e0a2f24840f6b1", "MD5sum": "d1c7641d6f837dbe853312489b78e8aa", "_user": "cran", "_type": "src", "_file": "FuzzyR_2.3.2.tar.gz", "_fileid": "a98cdcd283a2f61a7f19c77735b4f028533f7eb8310cabbca6852e2a40c116a4", "_filesize": 240982, "_sha256": "a98cdcd283a2f61a7f19c77735b4f028533f7eb8310cabbca6852e2a40c116a4", "_created": "2026-05-14T06:24:37.000Z", "_published": "2026-05-22T09:21:27.192Z", "_distro": "noble", "_jobs": [ { "job": 77351703978, "time": 129, "config": "linux-devel-x86_64", "r": "4.7.0", "check": 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