Aiming at the problem that the general rough sets can not present complete decision-making rules from limited data, the positive, negative and mixed consistent decision-making information system were defined. Method of obtaining rules for positive consistent system based on dominance relation was researched. Based on this, methods of obtaining rules for negative and mixed consistent systems based on dominance relation were put forward. A dominance rough sets method for consistent decision-making information system was then presented. The method was applied in the threat assessment of UCAV's targets. Decision-making information system for threat assessment of UCAV's targets was established. Preference of targets' attributes was analyzed. Decision-making algorithm was given, complexity of which was analyzed, and compared with dominance rough sets of Greco. Results show that the method is simple and rules can cover all values of the attributes.
Key words
consistent /
dominance /
rough sets /
UCAV /
threat assessment
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References
[1] Greco S, Matarazzo B, Slowinski R. Rough approximation of a preference relation by dominance relations[J]. European Journal of Operational Research, 1999, 117(2): 63-83.
[2] Zhai L Y, Khoo L P, Zhong Z W. A dominance-based rough set approach to Kansei engineering in product development[J]. Expert Systems with Applications, 2009, 36(1): 393-402.
[3] Blaszczynski J, Greco S, Slowinski R. Multi-criteria classification -- A new scheme for application of dominance-based decision rules[J]. European Journal of Operational Research, 2007, 181(3): 1030-1044.
[4] Greco S, Matarazzo B, Slowinski R. Rough approximation by dominance relations[J]. International Journal of Intelligent Systems, 2002, 17(2): 153-171.
[5] Greco S, Matarazzo B, Slowinski R. Rough sets theory for multi-criteria decision analysis[J]. European Journal of Operational Research, 2001, 129(1): 1-47.
[6] Yang X B, Xie J, Song X N, et al. Credible rules in incomplete decision system based on descriptors[J]. Knowledge-based Systems, 2009, 22(1): 8-17.
[7] Liou J J H. A novel decision rules approach for customer relationship management of the airline market[J]. Expert Systems with Applications, 2009, 36(3): 4374-4381.
[8] Slowinski R, Stefanowski J, Greco S, et al. Rough set based processing of inconsistent information in decision analysis[J]. Control Cybernetics, 2000, 29(1): 379-404.
[9] 张文修, 仇国芳. 基于粗糙集的不确定决策[M]. 北京: 清华大学出版社, 2005: 121-123.Zhang W X, Qiu G F. Uncertain Decision-Making Based on Rough Sets[M]. Beijing: Tsinghua University Press, 2005: 121-123.
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Footnotes
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