The full text of this article
Matroidal structure of covering-based rough sets through the upper approximation number
by Shiping Wang; William Zhu
International Journal of Granular Computing, Rough Sets and Intelligent Systems (IJGCRSIS), Vol. 2, No. 2, 2011
Abstract: Covering-based rough set theory is a generalisation of rough set theory. Matroids are based on linear algebra and graph theory, and have a variety of applications in many fields. In this paper, we introduce matroid theory to covering-based rough sets, and explore the matroidal structure and properties of covering-based rough sets. Specifically, we define the upper approximation number to establish the matroidal structure of covering-based rough sets. So many important concepts and methods in matroid theory can be employed to investigate covering-based rough sets. The rank plays a very important role in a matrix, so we use the rank function of the matroid induced by a covering to measure the covering. With the rank function, a pair of approximation operators, namely, matroid approximation operators, are constructed. This type of approximation operators not only inherits the properties of those traditional ones which are defined from the perspective of set theory, but also presents some new properties. Finally, the matroid upper approximations are compared with the second upper approximations in covering-based rough sets.
Online publication date: Wed, 26-Oct-2011
is only available to individual subscribers or to users at subscribing institutions.
Go to Inderscience Online Journals to access the Full Text of this article.
Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.
Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Granular Computing, Rough Sets and Intelligent Systems (IJGCRSIS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable).
See our Orders page to subscribe.
If you still need assistance, please email email@example.com