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

Citation counts:	Cited 11 times in TR Web of Science Cited 12 times in Scopus
Access Statistics:	317 Abstract Views, 4 File Downloads - Detailed Statistics
Created:	Mon, 12 Apr 2010, 19:02:53 EST by Sandra Dunoon

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