FUZZYMANAGER: a teaching and introductory environment for Fuzzy Logic and Fuzzy Clustering
| aut.researcher | MacDonell, Stephen Gerard | |
| dc.contributor.author | MacDonell, SG | |
| dc.contributor.author | Gray, AR, | |
| dc.contributor.author | Calvert, JM, | |
| dc.date.accessioned | 2011-09-08T09:02:40Z | |
| dc.date.available | 2011-09-08T09:02:40Z | |
| dc.date.copyright | 1999 | |
| dc.date.issued | 1999 | |
| dc.description.abstract | Using fuzzy logic, and associated techniques such as fuzzy clustering, in a teaching environment necessitates the availability of introductory and pedagogically appropriate tools. In a similar manner, introductory level tools may be necessary for practical applications where users are non-specialists in fuzzy theory, as is often the case. For these two scenarios, and many others, the tools that support the use of the modeling technique must satisfy sets of requirements concerning the interface, functionality, and documentation. Examples of these requirements can include the program’s ability to guide the user, without undue restrictions, through the necessary modeling procedures (as in a wizard interface) and explaining (both textually and graphically) the operation of the interface process. After outlining some of the desirable attributes for such tools that are intended to be used by these fuzzy novices, this paper describes the collection of tools collectively known as FUZZYMANAGER. Despite the name, which reflects its project management origins, the system is targeted towards any group of users without a particularly comprehensive or deep knowledge of fuzzy logic, who want an intuitive and graphical approach to fuzzy logic model building. As well as implementing standard inference options and methods, a clustering based algorithm for automatically deriving fuzzy systems from data (either membership functions, rules, or both may be extracted) is outlined. This component assists with the initial system creation process which can be an especially difficult activity for novices. | |
| dc.identifier.citation | Proceedings of the ICONIP'99/ANZIIS'99/ANNES'99/ACNN'99 International Workshop on Future Directions for Intelligent Systems and Information Sciences, Dunedin, New Zealand, pages 197 - 202 | |
| dc.identifier.uri | https://hdl.handle.net/10292/2031 | |
| dc.publisher | University of Otago | |
| dc.relation.uri | http://www.otago.ac.nz/researchpublications/?command=Search&sAOUname=Information%20Science | |
| dc.rights | NOTICE: this is the author’s version of a work that was accepted for publication. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in (see Citation). The original publication is available at (see Publisher's Version) | |
| dc.rights.accessrights | OpenAccess | |
| dc.title | FUZZYMANAGER: a teaching and introductory environment for Fuzzy Logic and Fuzzy Clustering | |
| dc.type | Conference Contribution | |
| pubs.organisational-data | /AUT | |
| pubs.organisational-data | /AUT/Design & Creative Technologies | |
| pubs.organisational-data | /AUT/PBRF Researchers | |
| pubs.organisational-data | /AUT/PBRF Researchers/Design & Creative Technologies PBRF Researchers | |
| pubs.organisational-data | /AUT/PBRF Researchers/Design & Creative Technologies PBRF Researchers/DCT C & M Computing |