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Applicable Analysis and Discrete Mathematics
Article . 2022 . Peer-reviewed
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Article . 2022
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Granular computing on basic digraphs

Authors: Chiaselotti G.; Gentile T.; Infusino F.;

Granular computing on basic digraphs

Abstract

In the present paper we investigate (p, q)-directed complete bipartite graphs ?K p,q, n-directed paths ?Pn and n-directed cycles ?C n from the perspective of Granular Computing. For each model, we establish the general form of all possible indiscernibility relations, analyze the classical rough approximation functions of rough set theory and provide a close formula for the global accuracy average. Finally, we completely determine the attribute dependency function and the global dependency average for both ?C n and ?Kp,q.

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Italy
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Keywords

granular computing, Digraphs, Rough Set Theory, Granular Computing, Information Tables, Approximation Measures., Applications of graph theory, Directed graphs (digraphs), tournaments, approximation measures, information tables, Reasoning under uncertainty in the context of artificial intelligence, digraphs, rough set theory

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selected citations
These citations are derived from selected sources.
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!
0
Average
Average
Average
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