The Ordered Weighted Averaging Operators

Theory and Applications

  • Ronald R. Yager
  • Janusz Kacprzyk

Table of contents

  1. Front Matter
    Pages i-ix
  2. Basic Issues in Aggregation

    1. Front Matter
      Pages 1-1
    2. Hung T. Nguyen, Vladik Kreinovich
      Pages 3-17
    3. Christer Carlsson, Robert Fullér, Szvetlana Fullér
      Pages 18-28
    4. Bernadette Bouchon-Meunier, Maria Rifqi
      Pages 29-35
    5. János Aczél, Günter Rote, Jens Schwaiger
      Pages 36-38
  3. Fundamental Aspects of OWA Operators

    1. Front Matter
      Pages 39-39
    2. F. Herrera, E. Herrera-Viedma
      Pages 60-72
    3. Michel Grabisch
      Pages 73-85
  4. Mathematical Issues and OWA Operators

  5. OWA Operators in Decision Analysis

    1. Front Matter
      Pages 121-121
    2. Ronald R. Yager, Maria Teresa Lamata
      Pages 123-138
    3. Kurt J. Engemann, Ronald R. Yager
      Pages 139-154
    4. Teresa C. Rubinson, Georgette Geotsi
      Pages 155-166
    5. Christer Carlsson, Robert Fullér, Szvetlana Fullér
      Pages 167-177
  6. OWA Operators in Multicriteria and Multiperson Decision Making

    1. Front Matter
      Pages 179-179

About this book

Introduction

Aggregation plays a central role in many of the technological tasks we are faced with. The importance of this process will become even greater as we move more and more toward becoming an information-cent.ered society, us is happening with the rapid growth of the Internet and the World Wirle Weh. Here we shall be faced with many issues related to the fusion of information. One very pressing issue here is the development of mechanisms to help search for information, a problem that clearly has a strong aggregation-related component. More generally, in order to model the sophisticated ways in which human beings process information, as well as going beyond the human capa­ bilities, we need provide a basket of aggregation tools. The centrality of aggregation in human thought can be be very clearly seen by looking at neural networks, a technology motivated by modeling the human brain. One can see that the basic operations involved in these networks are learning and aggregation. The Ordered Weighted Averaging (OWA) operators provide a parameter­ ized family of aggregation operators which include many of the well-known operators such as the maximum, minimum and the simple average.

Keywords

algorithms classification fuzzy fuzzy logic genetic algorithms learning machine learning tools uncertainty

Editors and affiliations

  • Ronald R. Yager
    • 1
  • Janusz Kacprzyk
    • 2
  1. 1.Iona CollegeNew RochelleUSA
  2. 2.Polish Academy of SciencesWarsawPoland

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-6123-1
  • Copyright Information Springer Science+Business Media New York 1997
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-7806-8
  • Online ISBN 978-1-4615-6123-1
  • About this book