Call for Papers for the 27th International Conference on Intuitionistic Fuzzy Sets is now open!
Conference: 5–6 July 2024, Burgas, Bulgaria • EXTENDED DEADLINE for submissions: 15 APRIL 2024.
Conference: 5–6 July 2024, Burgas, Bulgaria • EXTENDED DEADLINE for submissions: 15 APRIL 2024.
Issue:A framework for a prototype of an intuitionistic fuzzy expert system: Difference between revisions
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| title = The process of modeling economic problems presented as a generalized net with intuitionistic fuzzy logic elements | | title = The process of modeling economic problems presented as a generalized net with intuitionistic fuzzy logic elements | ||
| shortcut = | | shortcut = nifs/15/2/01-09 | ||
}} | }} | ||
{{issue/author | {{issue/author | ||
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| conference = 13<sup>th</sup> [[ICIFS]], Sofia, 9-10 May 2009 | | conference = 13<sup>th</sup> [[ICIFS]], Sofia, 9-10 May 2009 | ||
| issue = Conference proceedings, [[Notes on Intuitionistic Fuzzy Sets/15/2|"Notes on IFS", Volume 15 (2009) Number 2]], pages 1—9 | | issue = Conference proceedings, [[Notes on Intuitionistic Fuzzy Sets/15/2|"Notes on IFS", Volume 15 (2009) Number 2]], pages 1—9 | ||
| file = | | file = NIFS-15-2-01-09.pdf | ||
| format = PDF | | format = PDF | ||
| size = | | size = 222 | ||
| abstract = | | abstract = | ||
Today only a relatively simple or intentionally simplified real-world system could be modeled and precisely analyzed by application of the conventional mathematical and analytical methods. Most complex systems include the [[uncertainty]] as a characteristic of a variety of their parameters or attributes. To analyze such inherent ambiguity it is most natural to incorporate [[fuzzy logic|fuzzy]] or [[intuitionistic fuzzy logic]] (IFL) into the model. Due to the ability of IFL to handle the uncertainty, we suggest in this paper a framework for development of a prototype of an intuitionistic fuzzy expert system (IFES) that has to be able to capture, model and manage fuzzy data or the uncertainty of human or system behavior. As the contemporary systems usually have to deal with a great amount of data, the suggested framework does not rely on experts who will determine the IF degrees for each individual input object, but recommend that an IFES prototype should have automatic determination of the membership and non-membership degrees. | Today only a relatively simple or intentionally simplified real-world system could be modeled and precisely analyzed by application of the conventional mathematical and analytical methods. Most complex systems include the [[uncertainty]] as a characteristic of a variety of their parameters or attributes. To analyze such inherent ambiguity it is most natural to incorporate [[fuzzy logic|fuzzy]] or [[intuitionistic fuzzy logic]] (IFL) into the model. Due to the ability of IFL to handle the uncertainty, we suggest in this paper a framework for development of a prototype of an intuitionistic fuzzy expert system (IFES) that has to be able to capture, model and manage fuzzy data or the uncertainty of human or system behavior. As the contemporary systems usually have to deal with a great amount of data, the suggested framework does not rely on experts who will determine the IF degrees for each individual input object, but recommend that an IFES prototype should have automatic determination of the membership and non-membership degrees. |
Latest revision as of 20:47, 29 October 2009
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