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1)  weak fuzzy sum rule
弱模糊和规则
2)  local fuzzy sum rule
局部模糊和规则
1.
A generalized approximate mean value theorem and a generalized weak monotonicity result are obtained by using local fuzzy sum rule and generalized multifunctional mean value inequality in β smooth Banach spaces,so is a β subdifferential rule of the intersection composition of two set value maps.
在 β -光滑Banach空间中 ,利用局部模糊和规则、多个函数多方向中值不等式 ,把逼近中值定理、弱单调定理推广到多个函数的情形 ,并给出了集值映射方口积的次微分规则 。
3)  fuzzy rules
模糊规则
1.
A method of selecting fuzzy rules based on the clonal selection algorithm;
基于克隆选择算法的模糊规则提取方法
2.
Extract of fuzzy rules of the increase of Chinese economy based on fuzzy neural networks(part Ⅲ);
基于模糊神经网络提取我国经济增长的模糊规则(Ⅲ)
4)  fuzzy rule
模糊规则
1.
An approach of learning fuzzy rules based on learning automata arrays;
基于学习自动机阵列的模糊规则学习方法
2.
New algorithm for VLSI production sequencing problems based on fuzzy rule;
基于模糊规则的半导体生产线队列排序算法
3.
Identification of tea taste signals based on fuzzy rule generation algorithm;
基于模糊规则自动生成算法的茶味觉信号识别
5)  fuzzy if-then rules
模糊if-then规则
1.
A model fitted in with future price forecasting was established based on genetic algorithm and fuzzy IF-THEN rules.
基于遗传算法和模糊IF-THEN规则,建立适合期货价格预测的模型。
6)  vagueness of regulations
规则模糊
补充资料:模糊规则

模糊规则的形式为:if x is A then y is B
其中A和B为由论域X和Y上的模糊集合定义的语言值。“x is A”称为前提,“y is B”称为结论。

以上模糊规则可以简写为A → B。本质上模糊规则是定义在X × Y上的二元模糊关系R。A → B有
两种解释,一种是A耦合(coupled with)B:
<math>R=A \rightarrow B = A \times B = \int_{X \times Y}^{}tnorm(\mu_A (x), \mu_B (y))/(x,y)</math>
另一种是A导致(entails)B:
<math>R=A \rightarrow B = \bar{A} \cup B</math>
基于以上两种解释和不同的tnorm, tconorm算子,模糊规则可以有多种合法的计算公式。

说明:补充资料仅用于学习参考,请勿用于其它任何用途。
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