Using of Fuzzy Regulator in Clustering of Vaguely Define Objects

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Using of Fuzzy Regulator in Clustering of Vaguely Define Objects

Popis výsledku v původním jazyce

The clustering of objects is one of the areas of data mining. Recently are more and more processed data described by vague values. It seems useful to cluster these data also respecting their uncertainty. This paper concerns with clustering of such data.I define fuzzy object (object described by fuzzy sets), fuzzy similarity and dissimilarity of these ones and clustering of them. This paper follows with papers presented at previous conferences. These papers describe clustering of fuzzy objects using exttension principle (Zittau 2000) and generalization of fuzzy clustering methods (defined by J.C. Bezdek) for fuzzy objects (Zittau 2001). In this paper I use fuzzy objects and their basic characteristics and define similarity of fuzzy objects by suitablechoice of fuzzy regulator. The input is a pair of fuzzy objects and the output is a fuzzy set describing their similarity. Clustering exploiting this similarity was simulated in Matlab-Fuzzy Logic ToolBox.

Název v anglickém jazyce

Using of Fuzzy Regulator in Clustering of Vaguely Define Objects

Popis výsledku anglicky

The clustering of objects is one of the areas of data mining. Recently are more and more processed data described by vague values. It seems useful to cluster these data also respecting their uncertainty. This paper concerns with clustering of such data.I define fuzzy object (object described by fuzzy sets), fuzzy similarity and dissimilarity of these ones and clustering of them. This paper follows with papers presented at previous conferences. These papers describe clustering of fuzzy objects using exttension principle (Zittau 2000) and generalization of fuzzy clustering methods (defined by J.C. Bezdek) for fuzzy objects (Zittau 2001). In this paper I use fuzzy objects and their basic characteristics and define similarity of fuzzy objects by suitablechoice of fuzzy regulator. The input is a pair of fuzzy objects and the output is a fuzzy set describing their similarity. Clustering exploiting this similarity was simulated in Matlab-Fuzzy Logic ToolBox.

Druh

D - Stať ve sborníku

CEP obor

BA - Obecná matematika

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2002

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

10th Zittau Fuzzy Colloquium

ISBN

3-9808089-2-0

ISSN

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e-ISSN

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Počet stran výsledku

9

Strana od-do

311-319

Název nakladatele

n

Místo vydání

Zittau

Místo konání akce

Zittau

Datum konání akce

4. 9. 2002

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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