Matrix approaches to rough sets through vector matroids over fields
by Aiping Huang; Ziqiong Lin; William Zhu
International Journal of Granular Computing, Rough Sets and Intelligent Systems (IJGCRSIS), Vol. 3, No. 3, 2014

Abstract: Rough sets were proposed to deal with the vagueness and incompleteness of knowledge in information systems. There are many optimisation issues in this field such as attribute reduction. Matroids generalised from matrices are widely used in optimisation issues. Therefore, it is necessary to connect matroids with rough sets. In this paper, we take fields into consideration and introduce matrices to study rough sets through vector matroids. First, a matrix representing of an equivalence relation is proposed, and then a matroidal structure of rough sets over a field is presented by the matrix. Second, the circuits of the matroidal structure are studied through matrix null spaces. Third, over a binary field, we construct an equivalence relation from a matrix null space, and find that a family of equivalence relations and a family of sets, which any member is a collection of the minimal non-empty sets that are supports of members of null space of a binary dependence matrix, are isomorphic. In a word, matrices provide an interesting viewpoint to study rough sets.

Online publication date: Tue, 29-Jul-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
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:

    Username:        Password:         

Forgotten your 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 subs@inderscience.com