DocumentCode :
3046152
Title :
Information system hierarchical fuzzy evaluation based on bottom index clustering
Author :
Liu, Leilei ; Yang, Shiping
Author_Institution :
Coll. of Comput. Sci. & Inf., Guizhou Univ., Guiyang, China
fYear :
2010
fDate :
20-23 June 2010
Firstpage :
228
Lastpage :
233
Abstract :
When the information system risk is evaluated, it is of great importance to take various factors into account. Hierarchical fuzzy evaluation is a relatively valid method. However there is a great deal of difficulty in this algorithm. Therefore hierarchical fuzzy evaluation method based on bottom index clustering was introduced to assess information system in this paper. According to the attributes of the bottom indexes, atomic risk events of information system were clustered to calculate risk value of the bottom index. Then, use analytic hierarchy process to calculate the relative weight in every level of information system. Through these steps above, the comprehensive risk value of information system could be calculated by fuzzy logic method. The algorithm can solve the difficulty in combination evaluation practice and theoretical models preferably. It is more objective, effective and feasible than before.
Keywords :
decision making; fuzzy logic; information management; information systems; pattern clustering; risk management; analytic hierarchy process; atomic risk; bottom index clustering; fuzzy logic method; information system hierarchical fuzzy evaluation; information system risk; Clustering algorithms; Educational institutions; Fault trees; Fuzzy logic; Fuzzy systems; Information systems; Management information systems; Neural networks; Risk analysis; Risk management; FAHP; Information system; bottom index clustering; risk evaluation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Automation (ICIA), 2010 IEEE International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-5701-4
Type :
conf
DOI :
10.1109/ICINFA.2010.5512172
Filename :
5512172
Link To Document :
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