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Clustering and hierarchization of fuzzy systems

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Abstract

The readability of fuzzy models is related to their organizational structure and the corresponding rule base. On this basis, a new methodology for organizing the information, the Separation of Linguistic Information Methodology (SLIM), is developed. Based on its results, different algorithms are presented for different structures: the Parallel Collaborative Structure (PCS) - SLIM-PCS algorithm and the Hierarchical Prioritized Structure (HPS), SLIM-HPS algorithm. Finally, it is proposed a Fuzzy Clustering of Fuzzy Rules Algorithm (FCFRA) that allows the automatic organisation of the sets of fuzzy IF ... THEN rules of one fuzzy system in a Parallel Collaborative Structure, the probabilistic Fuzzy Clustering, and in a Hierarchical Prioritized Structure, the Possibilistic Fuzzy Clustering.

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Authors and Affiliations

  1. CETAV-universidade de Trás-os-Montes e Alto Douro, 5000-911, Vila Real, Portugal

    Paulo Salgado

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  1. Paulo Salgado
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Correspondence to Paulo Salgado.

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This work was supported by FCT – POSI/SRI/41975/2001

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Salgado, P. Clustering and hierarchization of fuzzy systems. Soft Comput 9, 715–731 (2005). https://doi.org/10.1007/s00500-004-0405-4

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  • DOI: https://doi.org/10.1007/s00500-004-0405-4

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