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INCREMENTALLY UPDATING APPROXIMATION IN INCOMPLETE INFORMATION SYSTEMS UNDER THE VARIATION OF OBJECTS

Tran Thi Thanh Huyen, Le Ba Dung, Nguyen Do Van, Mai Van Dinh

Abstract


Rough membership functions in covering approximation space not only give numerical characterizations of covering-based rough set approximations, but also establish the relationship between covering-based rough sets and fuzzy covering-based rough sets. In this paper, we introduce a new method to update the approximation sets with rough membership functions in covering approximation space. Firstly, we present the third types of rough membership functions and study their properties. And then, we consider the change of them while simultaneously adding and removing objects in the information system. Based on that change, we propose a method for updating the approximation sets when the objects vary over time.


Keywords


Rough Sets, covering-based rough set, Rough membership function, Incomplete Information Systems, approximation sets, Incremental Learning

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References


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DOI: https://doi.org/10.15625/1813-9663/36/4/14650 Display counter: Abstract : 51 views. PDF : 30 views.

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Journal of Computer Science and Cybernetics ISSN: 1813-9663

Published by Vietnam Academy of Science and Technology