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A fuzzy clustering method for the identification of fuzzy models for dynamic systems

机译:用于动态系统模糊模型识别的模糊聚类方法

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摘要

Fuzzy modeling is an important topic in fuzzy sets theory and applications. One particular fuzzy model structure, which can be used effectively to describe the behaviour of complex nonlinear systems, has been given by Takagi and Sugeno (1985). By means of a fuzzy clustering method, a new approach to the identification of this kind of fuzzy model is proposed, which integrates the structure and parameter identification steps, and/or the premise and consequence identification.
机译:模糊建模是模糊集理论和应用中的重要课题。 Takagi和Sugeno(1985)提出了一种特殊的模糊模型结构,可以有效地描述复杂非线性系统的行为。提出了一种基于模糊聚类的模糊模型识别方法,该方法将结构和参数的识别步骤,前提和后果的识别相结合。

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