Paper:
Language: English:

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

Received: January 12, 2007

Accepted: March 20, 2007

Keywords: fusion, mean operators, clustering

Journal ref: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.11, No.6 pp. 561-569, 2007

Abstract

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.

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