Article

Fuzzy data and information systems

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Reinhard ViertlAuthors Info & Claims

Proceedings of the 15th WSEAS international conference on Systems

Pages 83 - 85

Published: 14 July 2011 Publication History

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Abstract

Real quantitative data and other valuable informations are often not precise numbers but more or less nonprecise. This kind of uncertainty is also called fuzziness, and the related information is called fuzzy information. The best up-to-date description of this kind of data is by so-called "fuzzy numbers". In order to include such data in databases the databases have to be able to store fuzzy numbers in a suitable way.

References

[1]

J. Galindo: Handbook of Research on Fuzzy Information Processing in Data Bases, IGI Publishing, Hershey, 2008.

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[2]

G. Klir, B. Yuan: Fuzzy Sets and Fuzzy Logic, Prentice Hall, Upper Saddle River, NJ, 1995.

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[3]

F. Petry: Fuzzy Databases - Principles and Applications, Kluwer, Boston, 1996.

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[4]

R. Viertl: On the Description and Analysis of Measurements of Continuous Quantities, Kybernetika, Vol. 38 (2002).

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[5]

R. Viertl: Statistical Methods for Fuzzy Data, Wiley, Chichester, 2011.

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[6]

O. Wolkenhauer: Data Engineering, Wiley, New York, 2001.

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Index Terms

Fuzzy data and information systems
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Probabilistic reasoning
      2. Vagueness and fuzzy logic

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Published In

Proceedings of the 15th WSEAS international conference on Systems

July 2011

481 pages

ISBN:9781618040237

Editors:
Nikos Mastorakis
Technical University of Sofia, Bulgaria
,
Valeri Mladenov
Technical University of Sofia, Bulgaria
,
Zoran Bojkovic
University of Belgrade, Serbia
,
Fragkiskos Topalis
National Technical University of Athens, Greece
,
Kleanthis Psarris
The University of Texas at San Antonio

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World Scientific and Engineering Academy and Society (WSEAS)

Stevens Point, Wisconsin, United States

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Published: 14 July 2011

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Fuzzy vectors as a tool for modeling uncertain multidimensional quantities

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Fuzzy clustering algorithm for fuzzy data based on α-cuts

Fuzzy vectors as a tool for modeling uncertain multidimensional quantities

On fuzzy n-cell numbers and n-dimension fuzzy vectors

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