Situation Index Extraction Algorithm Based on Improved Discernibility Matrix and Expert Knowledge
TANG Cheng-Hua1,2, TANG Shen-Sheng3, XIE Yi4
1.Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin 541004 2.Guangxi Experiment Center of Information Science, Guilin University of Electronic Technology, Guilin 541004 3.Department of Engineering Technology, Missouri Western State University, St. Joseph, MO 64057, USA 4.School of Information Science and Technology, Sun Yat-sen University, Guangzhou 510275
Abstract Aiming at the problems of difficult and inefficient sample index extraction in the general reduction algorithm, rough set theory is introduced to extract situation index. The decision table information is reduced based on the discernibility matrix compression and classified selection, and the index selection is adjusted by combining the importance measure of the export knowledge. Meanwhile, a situation index extraction algorithm based on improved discernibility matrix and expert knowledge is proposed .It is analyzed and verified in the example of situation index system. Experimental results show that the proposed algorithm has good effect on the situation index reduction, and the extracted indexes are rational in the network security assessment. It provides a feasible solution for extracting the situation index.
TANG Cheng-Hua,TANG Shen-Sheng,XIE Yi. Situation Index Extraction Algorithm Based on Improved Discernibility Matrix and Expert Knowledge[J]. , 2014, 27(10): 907-914.
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