【摘要】 对于工业生产中的一些复杂、非线性系统 ,传统的建模方法很难描述其系统特性。但在实际生产中存在大量系统的输入输出数据 ,基于输入输出数据对复杂系统进行建模是一较好的途径。本文基于输入输出数据 ,提出一种决策树系统输入空间的划分方法 ,通过一定的数据训练 ,提取模糊规则 ,构成系统的模糊规则库 ,从而建立了非线性系统的模糊规则模型。仿真结果表明 ,该模型可以较好地描述系统的动态特性 ,同时也说明了该方法的快速性和有效性更多还原

【Abstract】 For dynamic systems with complex and nonlinear characteristics, the traditional modeling methods cannot describe its dynamic properties. In fact, there exists a large number of input output data of the complex systems, and it is an efficient approach to model based on input output data. This paper proposes a method for dividing the input space with decision tree regression. The fuzzy model is created through extracting the fuzzy rules from the training data. Simulational results show that the fuzzy model can describe the dynamic characteristics and that the method is quick and efficient.更多还原