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Communication Dans Un Congrès Année : 2003

Imprecise modelling using gradual rulesand its application to the classification of time series

Résumé

This paper prescrits an alternative to precise analytical modelling, by means of imprecise interpolative models. The model specification is based on gradual rules that express constraints that govern the interpolation mechanism. The modelling strategy is applied to the classification of time series. In this context, it is shown that gond recognition performance can be obtained with models that are highly imprecise.

Dates et versions

hal-03373366 , version 1 (11-10-2021)

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Sylvie Galichet, Didier Dubois, Henri Prade. Imprecise modelling using gradual rulesand its application to the classification of time series. 10th International Fuzzy Systems Association World Congress (IFSA 2003), Jun 2003, Istanbul, Turkey. pp.319--327, ⟨10.1007/3-540-44967-1_38⟩. ⟨hal-03373366⟩
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