Construction of aggregation functions from data using linear programming

Beliakov, Gleb 2009, Construction of aggregation functions from data using linear programming, Fuzzy sets and systems, vol. 160, no. 1, pp. 65-75.

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Title Construction of aggregation functions from data using linear programming
Author(s) Beliakov, Gleb
Journal name Fuzzy sets and systems
Volume number 160
Issue number 1
Start page 65
End page 75
Total pages 11
Publisher Elsevier
Place of publication Amsterdam, Netherlands
Publication date 2009-01
ISSN 0165-0114
1872-6801
Keyword(s) aggregation operators
fuzzy sets
quasi-arithmetic means
OWA
triangular norms
least absolute deviation
Summary This article examines the construction of aggregation functions from data by minimizing the least absolute deviation criterion. We formulate various instances of such problems as linear programming problems. We consider the cases in which the data are provided as intervals, and the outputs ordering needs to be preserved, and show that linear programming formulation is valid for such cases. This feature is very valuable in practice, since the standard simplex method can be used.
Language eng
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
HERDC collection year 2009
Copyright notice ©2008, Elsevier B.V.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30028308

Document type: Journal Article
Collection: School of Information Technology
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