DocumentCode
2385943
Title
An Efficient Elimination of Input Data in the OWA Aggregation
Author
Ahn, Byeong Seok
Author_Institution
ChungAng Univ., Seoul
fYear
2007
fDate
2-4 Nov. 2007
Firstpage
120
Lastpage
120
Abstract
In the paper, we present an efficient method for pruning multiple alternatives in the OWA aggregation. The proposed method intends to identify inferior alternatives per se and diminish the number of alternatives without any efforts to exploit the OWA operator weights from decision maker. The efficacy of the proposed method is verified by simulation analysis in which different levels of alternatives and different levels of criteria are used.
Keywords
data analysis; set theory; data filtering; data screening; decision making; finite sets; input data elimination; ordered weighted averaging operator; simulation analysis; Aggregates; Analytical models; Decision making; Educational institutions; Filtering; Linear matrix inequalities; Open wireless architecture; System testing; Uncertainty; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing, 2007. GRC 2007. IEEE International Conference on
Conference_Location
Fremont, CA
Print_ISBN
978-0-7695-3032-1
Type
conf
DOI
10.1109/GrC.2007.93
Filename
4403079
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