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采用模糊计算与神经计算相结合的方法，本文提出一种自适应模糊系统模型——AFS．AFS采用前向神经网络来实现模糊推理规则，运用模糊一致矩阵方法实现动态自适应以及最大关联隶属原则执行模糊决策．最后通过若干实例以说明AFS的性能．
Using a combination of fuzzy computation and neural computation, this paper presents an adaptive fuzzy system model - AFS. AFS uses the forward neural network to implement the fuzzy inference rules, uses the fuzzy consistent matrix method to realize the dynamic adaptive and the maximum associated subordination principle to implement the fuzzy decision. Finally, a number of examples to illustrate the performance of AFS.