一种高效的模糊规则自动生成方法

文中提出一种模糊规则自由生成方法。该方法借助Ｋ－Ｎｅａｒｅｓｔ－Ｎｅｉｇｈｂｏｒ的概念确定控制曲面的的关键点，然后根据关键点确定模糊划分，并由此构造模糊神经网络学习模糊规则。神经网络采用ＢＰ算法学习，在学习过程中可根据收剑情况适当增加模糊分区，并重构神经网络继续学习。该方法能生成较精简的规则集，并具有良好的收敛性和较快的收剑速度。

AN EFFICIENT METHOD OF FUZZY RULES GENERATION

A method for automatic generation of fuzzy rules is proposed, which finds out the essential points of the control surface by the concept of K Nearest Neighbor, and then uses these points to determine the fuzzy partitions so that it can construct a fuzzy neural network to learn fuzzy rules. The learning algorithm of the neural network is BP algorithm. During the training, the network can increase the number of fuzzy partitions properly due to the condition of the convergence, and then reconstructs itself to learn again. This method can generate a simple and effective rule set, and has a good convergent condition as well as a fast convergent speed.