On Fuzziness pp 343-347 | Cite as

On Fuzzy Data Analysis

  • Rudolf Kruse
  • Pascal Held
  • Christian Moewes
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 298)


Fuzzy systems can be found in nearly all industrial branches, e.g. automobile, control engineering, finance, medicine, logistics, telecommunications. Their advantage is their inherent simplicity. Fuzzy rule-based models often turn out to be useful and easily understandable in many real-world applications. In order to learn such models from data – may they be fuzzy or not – intelligent data analysis methods for learning and reasoning are necessary. Thus there is a need for fuzzy data analysis.

The aim of this paper is twofold: In the first part Rudolf Kruse presents some memoirs on early research in fuzzy data analysis and some anecdotes about Lotfi Zadeh in this context. The second part is donated to real-world applications of fuzzy methods and some thoughts about perspectives of fuzzy data analysis.


Fuzzy Logic Fuzzy System Fuzzy Control Fuzzy Measure Fuzzy Random Variable 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Rudolf Kruse
    • 1
  • Pascal Held
    • 1
  • Christian Moewes
    • 1
  1. 1.Fakultät für InformatikOtto-von-Guericke-Universität MagdeburgMagdeburgGermany

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