Application of Rough Classification of Multi-objective Extension Group Decision-making under Uncertainty
On account of the problem of incomplete information system in classification of extension group decision-making, this paper studies attribution reduction with decision-making function based on the group interaction and individual preferences assembly for achieving the goal of rough classification of multi-objective extension group decision-making under uncertainty. Then, this paper describes the idea and operating processes of multi-objective extension classification model in order to provide decision-makers with more practical, easy to operate and objective classification. Finally, an example concerning practical problem is given to demonstrate the classification process. Combining by extension association and rough reduction, this method not only takes the advantages of dynamic classification in extension decision-making, but also achieves the elimination of redundant attributes, conducive to the promotion on the accuracy and the reliability of the classification results in multi-objective extension group decision-making.
Keywords: extension group decision-making; matter-element analysis; extension association; rough set; attribution reduction
extension group decision-making; matter-element analysis; extension association; rough set; attribution reduction
- There are currently no refbacks.
If you have already registered in Journal A and plan to submit article(s) to Journal B, please click the CATEGORIES, or JOURNALS A-Z on the right side of the "HOME".
We only use three mailboxes as follows to deal with issues about paper acceptance, payment and submission of electronic versions of our journals to databases:
firstname.lastname@example.org; email@example.com; firstname.lastname@example.org
Copyright © 2010 Canadian Research & Development Centre of Sciences and Cultures
Address: 758, 77e AV, Laval, Quebec, H7V 4A8, Canada
Telephone: 1-514-558 6138