The aim of this study is to develop an operational model of an ordinal sum of triangular norms. The essence of this construct lies in the use of different t-norms (and/or t-conorms) defined over disjoint subintervals of the unit interval. The result of such aggregation is a highly versatile logic operator that can be easily adapted to the existing experimental evidence. We propose a genetic optimisation environment (Genetic Algorithms, GAs, in particular) to construct ordinal sums and show how the GA mechanism helps optimize subintervals and to allocate individual local t-norms. The application of the genetically designed ordinal sums is shown in case of Zimmermann–Zysno logic operator data.We also demonstrate the use of the ordinal sum to the construction of neuro-fuzzy systems; in this case we quantify the performance of ordinal sums to “standard” logic operators used in such models.

The Genetic Development of ordinal Sums

TAGLIAFERRI, Roberto;
2005-01-01

Abstract

The aim of this study is to develop an operational model of an ordinal sum of triangular norms. The essence of this construct lies in the use of different t-norms (and/or t-conorms) defined over disjoint subintervals of the unit interval. The result of such aggregation is a highly versatile logic operator that can be easily adapted to the existing experimental evidence. We propose a genetic optimisation environment (Genetic Algorithms, GAs, in particular) to construct ordinal sums and show how the GA mechanism helps optimize subintervals and to allocate individual local t-norms. The application of the genetically designed ordinal sums is shown in case of Zimmermann–Zysno logic operator data.We also demonstrate the use of the ordinal sum to the construction of neuro-fuzzy systems; in this case we quantify the performance of ordinal sums to “standard” logic operators used in such models.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/1065981
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