多标准决策表中发现概率规则的变精度粗糙集方法

Abstract

Abstract: An extension of variable precision rough sets model is proposed by dominance relation instead of indiscernibility relation,which can derive probabilistic rules from multi-criteria decision tables.The model can deal with possible inconsistencies in multi-criteria decision tables,obtain probabilistic decision rules made up of preference actions.Based on these rules,a preference model from example decision systems is inferred.Research results show that the minimal set of probabilistic decision rules obtained from a multi-criteria decision table by dominance relation has a smaller number of stronger rules and a smaller number of conditions.

Key words: variable precision rough set, multi-criterion decision table, dominance relation, probabilistic decision rules

CLC Number:

C931

PAN Yu, JIAN Li-rong, DA Qing-li. Variable Precision Rough Sets Methodology for Probabilistic Rules Discovery from a Multi-Criteria Decision Table[J]. Chinese Journal of Management Science, 2005, (1): 95-100.

References

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Variable Precision Rough Sets Methodology for Probabilistic Rules Discovery from a Multi-Criteria Decision Table

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