JACIII Vol.11 No.6 pp. 561-569
doi: 10.20965/jaciii.2007.p0561


Analysis of New Aggregation Operators: Mean 3Π

Andrei Doncescu*,**, Sebastien Regis***, Katsumi Inoue**,
and Richard Emilion****

*LAAS CNRS UPR 8001 Toulouse, France

**National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan

***University of West French Indies Point-a-Pitre, France

****University of Orleans, France

January 12, 2007
March 20, 2007
July 20, 2007
fusion, mean operators, clustering

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 suppose to have tools able to represent the knowledge in a mathematical form. One of the solutions is to use fuzzy logic operators. We present in this article an improvement of the triple Π operator introduced by Yager and Rybalov, which is called mean 3Π. Whereas triple Π is an operator completely reinforced, the presented operator is a mean operator, which makes it more robust to noise.

Cite this article as:
Andrei Doncescu, Sebastien Regis, Katsumi Inoue, and
and Richard Emilion, “Analysis of New Aggregation Operators: Mean 3Π,” J. Adv. Comput. Intell. Intell. Inform., Vol.11, No.6, pp. 561-569, 2007.
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Last updated on Feb. 25, 2021