DocumentCode :
2717106
Title :
Research on Data Attribute Reduction for Network Security Situation
Author :
Yanbo, Wang ; Huiqiang, Wang ; Xiufeng, Wang ; Ming, Yu
Author_Institution :
Coll. of Comput. Sci. & Technol., Harbin Eng. Univ., Harbin, China
fYear :
2012
fDate :
11-13 Aug. 2012
Firstpage :
589
Lastpage :
593
Abstract :
This paper firstly introduces the research object and key concept of rough set, the data reduction and classification is one of its core areas, Secondly analyzes the characteristics of rough set and limitations on data reduction, which usually is used jointly with other algorithm, and then introduce the rough set attribute reduction algorithm based on the original genetic algorithm, For the shortage of traditional algorithm, cross probability and variation probability and fitness function are further improved. Finally, the experiment proves the efficiency of improved algorithm is better than the traditional algorithm.
Keywords :
data reduction; genetic algorithms; pattern classification; probability; rough set theory; security of data; cross probability; data attribute reduction; data classification; fitness function; genetic algorithm; network security situation; rough set attribute reduction algorithm; variation probability; Algorithm design and analysis; Classification algorithms; Educational institutions; Genetic algorithms; Genetics; Sociology; Statistics; Attribute reduction; Genetic Algorithm; Rough Set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science & Service System (CSSS), 2012 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-0721-5
Type :
conf
DOI :
10.1109/CSSS.2012.587
Filename :
6394390
Link To Document :
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