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
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;
Conference_Titel :
Computational Aspects of Social Networks (CASoN), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-8785-1
DOI :
10.1109/CASoN.2010.53
