Uncertainty in Artificial Intelligence
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Generating the Structure of a Fuzzy Rule under Uncertainty
Juan Castro, Jose Zurita
Abstract:
The aim of this paper is to present a method for identifying the structure of a rule in a fuzzy model. For this purpose, an ATMS shall be used (Zurita 1994). An algorithm obtaining the identification of the structure will be suggested (Castro 1995). The minimal structure of the rule (with respect to the number of variables that must appear in the rule) will be found by this algorithm. Furthermore, the identification parameters shall be obtained simultaneously. The proposed method shall be applied for classification to an example. The {em Iris Plant Database} shall be learnt for all three kinds of plants.
Keywords: Fuzzy logic, automatic learning, environment, truth manintenance system.
Pages: 63-67
PS Link: ftp://pirata.ugr.es/pub/difuso/log/uai95.ps.Z
PDF Link: /papers/95/p63-castro.pdf
BibTex:
@INPROCEEDINGS{Castro95,
AUTHOR = "Juan Castro and Jose Zurita",
TITLE = "Generating the Structure of a Fuzzy Rule under Uncertainty",
BOOKTITLE = "Proceedings of the Eleventh Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-95)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1995",
PAGES = "63--67"
}


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