基于局部线性度量的模糊建模

Fuzzy Model ldentification Based on Local Linearity Measure

提出了一种高木－关野模糊逻辑系统的学习算法，该算法的核心是基于数据样本局部线性度量的聚类，它可以有效地确定规则数以及相应模糊逻辑系统的参数初值．通过对系统的参数进行优化，可以很好的描述输入输出变量间的关系．仿真实验说明了该方法的优越性．

A new Takagi-Sugeno type hay system modeling method is Proposed in this paper, which is based on local linearity measure of training data. The number of rules and their initial parameter values can be determined through this method. The relation between input/output variables can be approached much more accurately though parameter optimization. Finally a numerical example is used to illustrate the efficiency of this method.