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Complex Intelligent Systems and Their Applications pp 247–266Cite as

Reinforced Operators in Fuzzy Clustering Systems

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Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 41))

Summary

Knowledge-based systems need to deal with aggregation and fusion of data with uncertainty. To use many sources of information in numerical forms for the purpose of decision or conclusion, systems are supposed to have tools able to represent the knowledge in a mathematical form. One of the solutions is to use fuzzy logic operators.

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Author information

Authors and Affiliations

  1. LAAS-CNRS, University of Toulouse, 7, avenue du Colonel Roche, 31077, Toulouse, France

    Andrei Doncescu & Nabil Kabbaj

  2. Grimaag-Guadeloupe, Campus de Fouillole, B.P. 592, 97157, Pointe Pitre Cedex, France

    Sebastien Regis

Authors
  1. Andrei Doncescu
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  2. Sebastien Regis
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  3. Nabil Kabbaj
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Corresponding author

Correspondence to Andrei Doncescu .

Editor information

Editors and Affiliations

  1. North Campus, Ed. Omega, Department of Languages & Informatics Sy, Technical University of Catalonia, C/Jordi Girona 1-3-29, Barcelona, 08034, Spain

    Fatos Xhafa

  2. Fac. Information Engineering, Dept. Information &, Fukuoka Institute of Technology, Wajiro-higashi 3-30-1, Fukuoka, 811-0214, Japan

    Leonard Barolli

  3. , Department of Industrial and Systems Eng, University of Florida, Weil Hall 303, Gainesville, 32611, USA

    Petraq J. Papajorgji

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Doncescu, A., Regis, S., Kabbaj, N. (2010). Reinforced Operators in Fuzzy Clustering Systems. In: Xhafa, F., Barolli, L., Papajorgji, P. (eds) Complex Intelligent Systems and Their Applications. Springer Optimization and Its Applications, vol 41. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-1636-5_12

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