Skip to main content

Generating Simply Approximation Spaces by Using Decision Tables

Buy Article:

$107.14 + tax (Refund Policy)

The proposed from this paper is view the elimination of the attributes (columns) and the duplicate rows and removing superfluous of attributes values. We obtain the incomplete decision table which is different from the decision table and this table contains the necessary values to make decisions, and also in this paper we introduce new method to generate topology from decision table the degree of dependency between condition attributes and the decision attribute, reduction based on simply open sets. And also we introduce new concept namely, minimal simply open sets, and simply open sets. Also we introduce simply approximation space.

Keywords: Decision Table; Degree of Dependency; Minimal Simply Open Set; Rough Set; Simply Open Set Reduct; Topology

Document Type: Research Article

Affiliations: Department of Mathematics, Faculty of Science and Arts, Najran, University, P.O. Box, 1988, K.S.A.

Publication date: 01 October 2016

More about this publication?
  • Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
  • Editorial Board
  • Information for Authors
  • Submit a Paper
  • Subscribe to this Title
  • Terms & Conditions
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content