INTERPOLATIVITY OF ``AT LEAST--AT MOST'' MODELS OF MONOTONE FUZZY RULE BASES: MULTIPLE-INPUT CASE

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F12%3AA13014MG" target="_blank" >RIV/61988987:17610/12:A13014MG - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
INTERPOLATIVITY OF ``AT LEAST--AT MOST'' MODELS OF MONOTONE FUZZY RULE BASES: MULTIPLE-INPUT CASE
Original language description
Among the many desirable properties of fuzzy inference systems not all of them are known to co-exist. For instance, a system based on a monotone fuzzy rule base need not be monotonic and interpolative simultaneously. Recently, v{S}tv{e}pniv{c}ka and De Baets have investigated and shown the co-existence of the above two properties in the case of a fuzzy relational inference systems and the single-input-single-output (SISO) rule bases. An extension of these results to the multiple-input-single-output (MISO) case is not straight-forward owing to the lack of a natural ordering in higher dimensions. In this work, we study the MISO case and show that similar results are available when the monotone rule base is modeled based on at-most and at-least modifiers.
Czech name
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Czech description
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Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Uncertainty Modeling in Knowledge Engineering and Decision Making - Proc. of the 10th International FLINS Conference
ISBN
978-981-4417-73-0
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
598-607
Publisher name
World Scientific
Place of publication
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Event location
Istanbul
Event date
Jan 1, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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