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Noise Effects in Fuzzy Modelling Systems
Noise is source of ambiguity for fuzzy systems. Although being an important
aspect, the effects of noise in fuzzy modeling have been little investigated.
This paper presents a set of tests using three well-known fuzzy modeling
algorithms. These evaluate perturbations in the extracted rule-bases caused by
noise polluting the learning data, and the corresponding deformations in each
learned functional relation. We present results to show: 1) how these fuzzy
modeling systems deal with noise; 2) how the established fuzzy model structure
influences noise sensitivity of each algorithm; and 3) whose characteristics of
the learning algorithms are relevant to noise attenuation.Comment: 6 page