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Fuzzy Clustering in Modelling of Nonlinear Systems[editovat]

Author: Jan Procházka

Bakalářské práce 2008

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This paper explores fuzzy clustering methods and their usage for modeling nonlinear systems. We discuss methods fuzzy c-means and Gustafson-Kessel algorithm. Further we focused Takagi-Sugeno models, their principle and assembling using fuzzy clustering methods quoted above. Takagi-Sugeno models were tested on static nonlinear system where we verified aproximation capability and on dynamic discrete nonlinear system, where algorithms were searching for fuzyy clusters in four dimensions.

Bp 2008 prochazka jan.pdf