A brief logopedics for the data used in a Neuro-fuzzy milieu
A neuro-fuzzy reasoning algorithm, Fmta, which was constructed by the author, was applied to empiric data. This data comprised the ages, heights and weights of 126 schoolboys, and the aim was to explain and/or predict the weights of the system according to their ages and heights. Fmta yielded satisfactory results when compared with linear regression analysis, generalized mean and the Takagi-Sugeno algorithm.
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