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机构地区:[1]燕山大学继续教育学院,河北秦皇岛066004 [2]吉林大学数学学院,吉林长春130012
出 处:《系统工程与电子技术》2009年第6期1362-1365,共4页Systems Engineering and Electronics
基 金:国家自然科学基金重点项目资助课题(70431003)
摘 要:针对CC-OWA算子在数据集成过程中存在的问题,即集成后的数据失真、偏离均值,造成集成后的数据高于或低于被集成数据中的任何一个数,这样就不能保证算子的有界性。经过对集成过程的剖析,认为出现数据失真的根源在于CC-OWA算子中的"常平衡因子"。为了改进这一缺陷,首次提出了"变平衡因子"这一概念,并把改进后的算子称为C-DWA算子;并且研究了其性质,进一步就属性值以模糊语言或区间形式给出时,得到了决策排序步骤;通过实例分析对比阐明了C-DWA算子的优点和CC-OWA算子的缺陷。In the light of the problems in CC-OWA aggregation operators, namely distortion and deviating from mean values occur in the data to have been integrated, which causes the post-integrative data are higher (or lower) than any original data. As a result, the boundedness of the aggregation operator can not be guaranteed. It is caused by the "constant-balance factor" in CC-OWA aggregation operators. To solve the problem, the con- cept of "varying-balance factor" is proposed, and the characteristics of the C-DWA operator are studied. Based on this operator, the approach to solving decision-making steps is developed, in which the attribute weights are completely known and the attribute values are interval numbers or in the forms of fuzzy linguistic respectively. Finally, some examples are applied to expound the advantages of C-DWA operators and the defects of CC-OWA operators.
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