介绍了一种新的规则自提取和简化的模糊模型算法，该算法由3个步骤组成：首先，通过构造一个模糊软划分判别准则对输入输出空间进行模糊划分，得到最佳分类数，从而得到了最佳的规则数；其次，根据最佳规则数和神经网络来构造初始的模糊模型；第三，通过运用模糊相似分析法，可以得到计算2个模糊集相似度的方程，从而根据事先确定的阈值来合并相似的模糊集。这样就得到了一个既满足对精度的要求又简单且具有可解释性的模糊系统。最后，用该算法对我国全要素生产力进行了模糊规则的提取。

In this paper, a fuzzy model algorithm for a rule-base self-extraction and simplification is introduced. The method consistes of three steps: The first step is to classify the out-in space by constructing a fuzzy partition validity index, then the optimal number of dusters and, hence, the optimal number of rules are obtained; The second step is to construct the initial fuzzy system based on the optimal number of rules and neural networks; The third step is to get the function of computing similarity of fuzzy sets by fuzzy similarity analysis method. The similar fuzzy sets are merged to create a common fuzzy set in rule base based on threshold value. Thus a fuzzy system with interpretability and simplicity is obtained. At last, the fuzzy rules of productivity factor of China is extracted by the fuzzy system.