Scheduled System Maintenance on May 29th, 2015:
IEEE Xplore will be upgraded between 11:00 AM and 10:00 PM EDT. During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

Dominance-based rough set approach to incomplete fuzzy information system

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Lihua Wei ; Sch. of Comput. Sci. & Technol., Nanjing Univ. of Sci. & Technol., Nanjing ; Zhenmin Tang ; Xibei Yang ; Lili Zhang

Although many extended rough set models have been successfully applied into the incomplete information system, most of them do not take the incomplete information system with initial fuzzy data into account. This paper thus presents a general framework for the study of dominance-based rough set model in the incomplete fuzzy information systems. First, the traditional dominance relation is expanded in the incomplete fuzzy information system. We then present the dominance-based rough approximations by the rough fuzzy technique. Finally, we propose two types of knowledge reductions, relative lower and upper approximate reducts, which can be used to induce simplified decision rules from the incomplete fuzzy decision table. We also present the judgement theorems and discernibility functions which describe how relative lower and upper approximate reducts can be calculated. We employ some numerical examples in this paper to substantiate the conceptual arguments.

Published in:

Granular Computing, 2008. GrC 2008. IEEE International Conference on

Date of Conference:

26-28 Aug. 2008