1) Positive fuzzy number
正模糊数
2) normal fuzzy number
正态模糊数
1.
In order to soften partition boundary of the domain, the relational fuzzy c means algorithm is adopted to determine two parameters of normal fuzzy numbers, then the normal fuzzy number model is adopted to partition the domain of the quantitative attributes and a series of linguistic value association rules are generated.
为了软化论域的划分边界 ,应用相关的模糊 c-方法 (rela-tional fuzzy c- means,简称 RFCM)算法确定正态模糊数的两个参数 ,并借助正态模糊数模型来划分数量属性的论域 ,由此生成一系列的语言值关联规则 。
2.
A new pricing approach to real option is thus proposed to transform the forecast intervals evaluated by experts into some normal fuzzy numbers with the lattice closenes.
提出了将预期现金流收益现值的专家评估区间转化成正态模糊数并利用格贴近度构造权向量的一种新的实物期权定价方法,验证了利用正态模糊数估计现金流收益现值的合理性。
3.
The linguistic variable of the evaluation value and weight vectors is modeled by the normal fuzzy number,and the decision making framework based on the linguistic operator is established by the weighted mean method.
采用正态模糊数描述指标级别和权重的语言值,并通过加权平均方法构建了基于语言算子的决策框架。
3) normal fuzzy function
正规模糊函数
4) the Fuzzy numerical tangent function
模糊数值正切函数
1.
This paper discusses the Fuzzy numerical tangent function and Fuzzy numerical cotangent function based on the extension theory,and further studies their basic characteristics.
利用扩展原理引入了模糊数值正切函数与余切函数 ,并研究了这两种模糊函数的基本性
5) Fuzzy number-valued sinusoidal function
模糊数值正弦函数
补充资料：数不胜数
1.数也数不清。形容很多。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条