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Caracterizing k-Additive Fuzzy Measures

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Technologies for Constructing Intelligent Systems 2

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 90))

Abstract

Recently, Grabisch has proposed the concept of k-additive measures to cope with the complexity problem involved by the use of fuzzy measures [8]. The concept has proven to be useful in multicriteria decision making, since it brings a model which is both flexible and simple to use.

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Author information

Authors and Affiliations

  1. Departamento de Estadística, I.O. y D.M., Calvo Sotelo s/n, 33007, Oviedo, Spain

    Pedro Miranda

  2. Université Pierre et Marie Curie- LIP6, 8, rue du Capitaine Scott, 75015, Paris, France

    Michel Grabisch

Authors
  1. Pedro Miranda
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  2. Michel Grabisch
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Editor information

Editors and Affiliations

  1. CNRS, LIP6, Université Paris VI, 8 rue du Capitaine Scott, 75015, Paris, France

    Bernadette Bouchon-Meunier

  2. Facultad de Informática, Universidad Politécnica de Madrid, Campus de Montegancedo, 28660, Boadilla del Monte, Madrid, Spain

    Julio Gutiérrez-Ríos

  3. Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, 28040, Madrid, Spain

    Luis Magdalena

  4. Machine Intelligence Institute, Iona College, 10801, New Rochelle, NY, USA

    Ronald R. Yager

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© 2002 Springer-Verlag Berlin Heidelberg

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Miranda, P., Grabisch, M. (2002). Caracterizing k-Additive Fuzzy Measures. In: Bouchon-Meunier, B., Gutiérrez-Ríos, J., Magdalena, L., Yager, R.R. (eds) Technologies for Constructing Intelligent Systems 2. Studies in Fuzziness and Soft Computing, vol 90. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1796-6_17

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  • DOI: https://doi.org/10.1007/978-3-7908-1796-6_17

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-2504-6

  • Online ISBN: 978-3-7908-1796-6

  • eBook Packages: Springer Book Archive

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