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Improving Group Decision Support Systems using Rough Set

by Mohamed Eisa
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 69 - Number 2
Year of Publication: 2013
Authors: Mohamed Eisa
10.5120/11812-7473

Mohamed Eisa . Improving Group Decision Support Systems using Rough Set. International Journal of Computer Applications. 69, 2 ( May 2013), 9-13. DOI=10.5120/11812-7473

@article{ 10.5120/11812-7473,
author = { Mohamed Eisa },
title = { Improving Group Decision Support Systems using Rough Set },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 69 },
number = { 2 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 9-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume69/number2/11812-7473/ },
doi = { 10.5120/11812-7473 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:29:10.051281+05:30
%A Mohamed Eisa
%T Improving Group Decision Support Systems using Rough Set
%J International Journal of Computer Applications
%@ 0975-8887
%V 69
%N 2
%P 9-13
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, a proposed Group Decision Support Systems model based on Rough Set is presented. The model improves decision making process by using rough set as a tool for knowledge discovery on decision support system, where the same feature may evaluate by one decision maker as good and by another one as medium, in this case inconsistent will appear in decision problem. To cope with this problem, the model will be used to reduce inconsistent after computing lower and upper approximations. Moreover, the classification accuracy of the rough set with a single classifier and multiple classifiers was compared. These results indicate that, the model improve the classification accuracy for data sets, rather than using single and multiple classifiers.

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Index Terms

Computer Science
Information Sciences

Keywords

Group Decision Support Systems Rough set Classification accuracy

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