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用粗集理论挖掘项目审查(评估)中的专家共识 被引量:2

Mining of Common Decision Knowledge of Specialists in Project Evaluation Using Rough Set Theory
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摘要 为了改进现有的评估方法,在项目审查(评估)中,采用基于决策表的粗糙集模型算法,从众多专家的决策中找到潜在地存在于各个决策中的、公认的决策共识作为项目审查的依据和最终结果.应用该算法可以找出条件属性集中对决策最为重要的影响因素,确定实际应用中的数据采集规则.提出采用条件属性集的约简作为新的条件属性集的方法,以降低决策的复杂性,防止决策者个体的舞弊行为. The rough set model algorithm based on the decision table was used in project evaluation to acquire common decision knowledge from decisions of many specialists as the criterion and the final result of project evaluation so as to improve the existing evaluation algorithm. With this algorithm, the most important factors for decision-making in a condition attribute set and the rules of data mining can be determined. In addition, it was proposed that the reduction of the condition attribute set is used as a new condition attribute set in order to reduce the complexity of decision-making and avoid the irregularity of the individual of decision-makers under the precondition of not influencing the result of decision-making.
作者 蓝敏
出处 《西南交通大学学报》 EI CSCD 北大核心 2005年第1期85-89,共5页 Journal of Southwest Jiaotong University
关键词 粗糙集模型算法 项目评估 数据挖掘 rough set model algorithm project evaluation data mining
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参考文献3

  • 1Pawlak Z. Rough set theory and its application to data analysis[J]. Cybernetics and Systems, 1998, 29: 661-688.
  • 2Pawlak Z. Rough set: theoretical aspects of reasoning about data[M]. Dordrecht: Kluwer Academic Pub, 1991. 3-56.
  • 3Jelonek J, Krawiee K, Slowinski R. Rough set reduction of attributes and their domains for neural networks [ J ].Computational Intelligence, 1995, 11:339-347.

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