1) Simple Control Regular
简单模糊规则
3) simple rule
简单规则
1.
This paper introduces some forming mechanism of the complex network,and enumerates several typical examples for the forming of the complex network based on the simple rules firstly.
首先介绍了复杂网络的一些形成机制,列举一些由简单规则形成复杂系统的典型例子。
4) simple fuzzy control
简单模糊
1.
Adaptive fuzzy control,on the basis of simple fuzzy control,is constructed by fuzzily online-ajusting the gains,and is used in the VAV terminal unit.
通过增加在线模糊调整量化增益和比例增益,在简单模糊控制理论的基础上架构成自适应模糊控制理论,并把其运用于VAV空调末端装置的控制。
5) 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)
6) 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
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。
参考词条