摘要
模糊属性值的规范化是模糊多属性决策分析中的一个基础性问题。本文针对由有界模糊数表示的收益类属性值和成本类属性值,基于模糊数的扩展线性运算和期望值算子,提出了三种规范化方法,同时说明了它们各自的特点,并对这些方法进行了比较。最后给出了算例。
Normalizing of fuzzy attribute values is a basic in fuzzy multiple attribute decision making. This paper presented three methods to normalize profit attribute values and cost attribute values denoted by bounded fuzzy numbers based on the fuzzy linear operation and the expected value operator of fuzzy numbers. The different characteristics of three methods are explained, and a comparison among these methods are also given. Finally, a numerical example is given to illustrate these methods.
出处
《模糊系统与数学》
CSCD
北大核心
2006年第2期97-102,共6页
Fuzzy Systems and Mathematics
基金
国家自然科学基金资助项目(10501009)
关键词
模糊属性值的规范化
模糊多属性决策
有界模糊数
模糊线性运算
期望值算予
Normalizing of Fuzzy Attribute Values
Fuzzy Multiple Attribute Decision Making^Bounded Fuzzy Number
Fuzzy Linear Operation
Expected Value Operator
