The rule base including 49 fuzzy rules is also established.
还建立了包括49 个模糊规则的规则库。
The hyperbolic model can be easily derived from a set of fuzzy rules.
这种模型是一种模糊模型，可以很容易由几条模糊规则得出。
Automatic generation of fuzzy rules is a key technique in fuzzy control.
模糊规则自动生成是模糊控制的关键性技术之一。
The fuzzy controller with an intuitive structure has a small number of fuzzy rules.
该模糊控制器规则总数少，直观性强。
An adaptive control algorithm is given to adjust fuzzy rules to adapt system change.
同时还给出了一种自适应控制算法，利用它可以调整模糊规则以适应系统的时变性。
Hybrid fuzzy logic method used fuzzy rules and crisp data to identify a fuzzy logic system.
混合模糊逻辑方法就是利用模糊规则和对象输入输出的观测数据来辨识一个模糊逻辑系统。
The weights of the weighted fuzzy rules can be acquired by training the fuzzy neural network.
训练好的模糊神经网络即为一个模糊推理器。
The fuzzy rules of the factors are discussed and it predicts the ridership of the mass transit.
确定各因素的模糊规则，采用模糊推理预测公交分担率。
This paper proposes a new method to find fuzzy rules using an improved clonal selection algorithm.
提出了利用改进的克隆选择算法发现模糊规则的方法。
By combination of expert experience and fuzzy identification, the fuzzy rules become more reliable.
在建立模糊规则时，应用了专家经验与模糊辨识相结合的方法，使规则更加合理可信。
On the basis of fuzzy clustering and rough set, an algorithm for extracting fuzzy rules was proposed.
提出了一种基于模糊软分类和粗糙集理论来提取模糊规则的一种算法。
Therefore, researching automatic generation of fuzzy rules has important values in the theory and application.
因此研究模糊规则的自动生成有着重要的理论和应用价值。
Using the method, the fuzzy rules and crisp data were preprocessed and the ideal initial parameters were given.
该方法对模糊规则和观测数据进行了预处理，给出系统模型的初始结构和参数。
The classical methods of extracting fuzzy rules is determined by experience, which is complex and more difficult.
对于模糊规则的获取，传统的方法是凭经验来确定，这种方法复杂且难度大。
Based on above work, in the third part, actualize fuzzy rules automatic generation applying fuzzy RBF neural net.
第三部分，在前述工作基础上，用模糊rbf神经网络实现模糊规则的自动获取。
The context network matches the premises of fuzzy rules and produces a matching factor as outputs for each rules.
特征网络用来产生模糊规则的前件，相应于每条规则的适用度。
Proposes a classification algorithm based on simplified fuzzy rules base combining fuzzy clustering with rough set.
结合模糊聚类和粗糙集提出了一种基于精简的模糊规则库分类算法。
Secondly, the fuzzy image data are enhanced for special times, which could reduce the uncertainty in the fuzzy rules.
接着进行多次迭代的图像模糊增强，主要目的是减小图像模糊判决的不确定性；
Although there are many kinds of methods to optimize compute, it is difficult to artificially set fuzzy rules, even impossible.
尽管用各种方法进行优化计算，人工设定模糊规则还是很困难的，甚至是不可能的。
A soft sensor modeling method is presented which selects optimal fuzzy rules by tuning the radius of a subtractive cluster center.
提出了一种通过调整减法聚类半径优选模糊规则的软测量建模方法。
Aiming at the familiar SISO thermodynamic system, the general structural style for inverse dynamics fuzzy rules model is presented.
针对常见的单输入单输出的热力系统，提出了逆动力学模糊规则模型的一般结构形式。
In this fuzzy model, the fuzzy rules are generated on every fuzzy division layer with different fuzzy partitions from other layers.
在该模糊模型中，因各层的分割数相异，而使得该模糊规则具有不同特性。
In the research of reasoning machine, a FNN reasoning method is used to solve the problem of collision and inefficiency in the fuzzy rules reasoning.
在对推理机制的研究中，采用模糊神经网络推理方法解决了模糊规则推理时存在的冲突和低效率问题。
A function for measuring clustering validity based on the fuzzy clustering algorithm is defined with which the number of fuzzy rules can be determined.
在模糊聚类算法的基础上，提出了一个衡量聚类有效性的函数，以确定模糊规则的数目。
Computer fuzzy control with control table may reduce the level of memory size and computing speed. Control table can be off-line gained by fuzzy rules.
通过控制表实现计算机模糊控制，可以降低对计算机内存容量和速度的要求，控制表根据人们对控制对象的认识和操作经验确定的模糊控制规则离线处理。
Inverse dynamics fuzzy rules model is the mathematical model about object movement disciplinarian which can be used for fuzzy controller design directly.
系统逆动力学模糊规则模型，是一类可以直接用于模糊控制器设计的关于对象运动规律的数学模型。
Inverse dynamics fuzzy rules model is the mathematical model about object movement disciplinarian which can be used for fuzzy controller design directly.
系统逆动力学模糊规则模型，是一类可以直接用于模糊控制器设计的关于对象运动规律的数学模型。
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