关键词: 模糊聚类, 满意聚类, 支持向量机, 多模型

Abstract: An improved satisfactory clustering algorithm is presented to solve the commonly existed problems in fuzzy clustering algorithm，such as giving clustering number in advance and slow convergence.Using improved satisfactory clustering algorithm，a nonlinear system can be quickly divided into several fuzzy parts，and the sub-models are trained by support vector machine，which are combined by the degrees of membership of input variables.Finally，the industrial simulation shows the efficiency，the accuracy and the rapidity of the method proposed in this paper.

Key words: fuzzy clustering, satisfactory clustering, support vector machine, multi-model