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A method for weight assignment by Dominance-based Rough Sets Approach

Authors: Liu Bin; Zhang Rong; Liu Si-feng;

A method for weight assignment by Dominance-based Rough Sets Approach

Abstract

In many real problems, it does not consider the ranking characteristic of criteria to make multi-criteria decision with classical rough sets theory. By Dominance-based Rough Sets Approach (DRSA), this paper develops methods for weight assignment respectively under two settings, with decision sorting classes and without decision sorting classes. Compared to present methods, the advantage of our methods is that: from descriptive set of the given problem, extracts the inherent rules implied by alternatives dominance relations with respect to each attribute, and avoids excessively depending on experts' experience; realizes completely data driving. Finally an example illustrates our methods are effective and reasonable.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
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