Skip to main content

Representations

  • Chapter
  • First Online:
Discrete Fuzzy Measures

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 382))

  • 391 Accesses

Abstract

This chapter discusses various representations of set functions with a view toward practical applications of fuzzy measures. This includes Möbius and interaction representations, as well as vector representations that allow various calculations to be performed systematically and efficiently using software. Fuzzy measure transformations between the different representations in matrix-vector form are specified, which are also convenient for computer implementation. Lastly we address the marginal contributions representation and express various quantities with its help.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Grabisch, M.: The representation of importance and interaction of features by fuzzy measures. Pattern Recognit. Lett. 17(6), 567–575 (1996)

    Article  Google Scholar 

  2. Grabisch, M.: k-Order additive discrete fuzzy measures and their representation. Fuzzy Sets Syst. 92, 167–189 (1997)

    Article  MathSciNet  Google Scholar 

  3. Grabisch, M.: The interaction and Möbius representation of fuzzy measures on finite spaces, k-additive measures: a survey. In: Grabisch, M., Murofushi, T., Sugeno, M. (eds.) Fuzzy Measures and Integrals. Theory and Applications, pp. 70–93. Physica, Heidelberg (2000)

    Google Scholar 

  4. Grabisch, M.: Set Functions, Games and Capacities in Decision Making. Springer, Berlin (2016)

    Book  Google Scholar 

  5. Grabisch, M., Marichal, J.-L., Roubens, M.: Equivalent representations of set functions. Math. Oper. Res. 25, 157–178 (2000)

    Article  MathSciNet  Google Scholar 

  6. Grabisch, M., Murofushi, T., Sugeno, M. (eds.): Fuzzy Measures and Integrals. Theory and Applications. Physica, Heidelberg (2000)

    Google Scholar 

  7. Marichal, J.-L.: Aggregation of interacting criteria by means of the discrete Choquet integral. In: Calvo, T., Mayor, G., Mesiar, R. (eds.) Aggregation Operators. New Trends and Applications, pp. 224–244. Physica, Heidelberg (2002)

    Google Scholar 

  8. Marichal, J.-L.: k-Intolerant capacities and Choquet integrals. Eur. J. Oper. Res. 177(3), 1453–1468 (2007)

    Article  MathSciNet  Google Scholar 

  9. Wu, J.-Z., Beliakov, G.: Marginal contribution representation of capacity based multicriteria decision making. In: Under Review (2018)

    Google Scholar 

  10. Wu, J.-Z., Beliakov, G.: Nonadditivity index and capacity identification method in the context of multicriteria decision making. Inf. Sci. 467, 398–406 (2018)

    Article  MathSciNet  Google Scholar 

  11. Wu, J.-Z., Beliakov, G.: Nonmodularity index for capacity identifying with multiple decision criteria. In: Under Review (2018)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gleb Beliakov .

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Beliakov, G., James, S., Wu, JZ. (2020). Representations. In: Discrete Fuzzy Measures. Studies in Fuzziness and Soft Computing, vol 382. Springer, Cham. https://doi.org/10.1007/978-3-030-15305-2_4

Download citation

Publish with us

Policies and ethics