DocumentCode
3106452
Title
Granular Computing Reduction Method for SDG Model
Author
Gang, Xie ; Wen, Wang ; Zehua, Chen
Author_Institution
Dept. of Inf. Eng., Taiyuan Univ. of Technol., Taiyuan, China
fYear
2010
fDate
26-28 Sept. 2010
Firstpage
204
Lastpage
207
Abstract
Granular computing, provides a new solution for qualitative SDG fault diagnosis not only in philosophy but also in technique. In this paper, granular matrix-based knowledge reduction algorithm is applied to simplify SDG model which transform the attribute reduction into simple binary matrix operation. The research fruits show the effective integration of SDG model and granular computing.
Keywords
directed graphs; fault diagnosis; knowledge engineering; matrix algebra; SDG model; attribute reduction; binary matrix operation; granular computing reduction method; granular matrix based knowledge reduction algorithm; qualitative SDG fault diagnosis; signed directed graph; Computational modeling; Data models; Decision making; Encoding; Fault diagnosis; Mathematical model; Solid modeling; SDG(signed directed graph); attribute reduction; granular computing; granular matrix;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Aspects of Social Networks (CASoN), 2010 International Conference on
Conference_Location
Taiyuan
Print_ISBN
978-1-4244-8785-1
Type
conf
DOI
10.1109/CASoN.2010.53
Filename
5636845
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