Titlebook: ;

evasive

FLORA

Granularity and Specificity in Fuzzy Rule-Based Systems,aining data. The trade-offs between granularity, specificity, interpretability, and efficiency are examined for rule-bases produced in each of these manners. An algorithm that combines rule learning with region merging is introduced to incorporate beneficial features of both the heuristic and learning approaches to producing fuzzy models.

CHIP

Granular Computing978-3-7908-1823-9Series ISSN 1434-9922 Series E-ISSN 1860-0808

osteocytes

Vertebra

Neue Einleitung 1969: Nach 15 Jahrenctors. For these systems, the representation of uncertainty as confidence intervals or the ellipsoids offers significant advantages over the more traditional approaches with probabilistic representation of noise. While the filtered-white-Gaussian noise model can be defined on grounds of mathematical

Collision

Was Passiert auf dem Arkturus Gerade Jetzt? of all values of the parameter vector that are acceptable in the sense that all errors between the experimental data and the corresponding model outputs lie between known lower and upper bounds. This corresponds to what is known as bounded-error estimation or membership-set estimation. Most of the

占卜者

可卡

Fsh238

Metapopulationsanalyse auf Rasterdatenbasisa unique crisp/fuzzy subset of data, representing the “nearest” neighborhood, is a binary relation between the object and data spaces. “Nearest” neighborhood consists of data that are semantically related to ., and represents an elementary granule (atoms) of the system under consideration. This pape

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