Data Mining Using a Probabilistic Weighted Ordered Weighted Average (PWOWA) Operator

  • H. B. Mitchell
Chapter
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 123)

Abstract

The Weighted Ordered Weighted Average (WOWA) operator is a powerful operator used for aggregating a set of M input arguments which may derive from different sources. The WOWA operator allows the user to take into account both the importance or reliability of the different information sources and the relative position of the argument valnes. In this chapter we describe a powerful new-probabilistic weighted ordered weighted average (PWOWA) operator, which is simple and fast to implement, robust and whose parameters may all be given a direct physical interpretation. The chapter concludes with a demonstration of the new operator in a practical example involving lossless image compression.

Keywords

Aggregation Operator Lossless Compression Ordered Weighted Average Basic Predictor Weighted Average Operator 
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 2003

Authors and Affiliations

  • H. B. Mitchell
    • 1
  1. 1.Intelligent Centers Department (Section 3424) Signal Processing and Computer DivisionElta Electronics Industries Ltd.AshdodIsrael

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