Deakin University
Browse

File(s) not publicly available

k–Order Fuzzy Measures and k–Order Aggregation Functions

Version 2 2024-06-06, 04:28
Version 1 2019-06-28, 14:57
chapter
posted on 2024-06-06, 04:28 authored by Gleb BeliakovGleb Beliakov, Simon JamesSimon James, JZ Wu
© 2020, Springer Nature Switzerland AG. This chapter studies simplifying assumptions on fuzzy measures that reduce the number of parameters required for their definition. In each case this is achieved by considering only subsets of up to cardinality k in one or another representation, leading to simplifications in their construction, learning and interpretation. However unlike the case of additive and symmetric fuzzy measures, this still leaves scope for modelling complex input interaction, a key benefit of using fuzzy measures.

History

Volume

382

Pagination

193-203

ISSN

1434-9922

eISSN

1860-0808

ISBN-13

9783030153045

Publication classification

BN Other book chapter, or book chapter not attributed to Deakin

Publisher

Springer

Place of publication

Cham, Switzerland

Title of book

Discrete Fuzzy Measures

Series

Studies in Fuzziness and Soft Computing

Usage metrics

    Research Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC