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Decomposition of a greenhouse TS-Fuzzy model by clustering process

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This paper presents a fuzzy c-means clustering method for decompose a T-S fuzzy system. This technique is used to organize the fuzzy greenhouse climate model into a new structure more interpretable, as in the case of the physical model. This new methodology was tested to split the inside greenhouse air temperature and humidity flat fuzzy models into fuzzy sub-models. These fuzzy sub-models are compared with its counterpart’s physical sub-models. This algorithm is applied to the T-S fuzzy rules. The results are several clusters of rules where each cluster is a new fuzzy sub-system. This is a generalized Probabilistic Fuzzy C-Means (PFCM) algorithm applied to TS-Fuzzy System clustering. This allows automatic organization of one fuzzy system into a multimodel Hierarchical Structure.

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Fuzzy clustering Relevance

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Salgado, Paulo; Igrejas, Getúlio (2007). Decomposition of a greenhouse TS-Fuzzy model by clustering process. In 4.ª Conferência de Engenharia "Engenharia' 2007 - Inovação e Desenvolvimento. Covilhã

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