Noise Effects in Fuzzy Modelling Systems
<|reference_start|>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.<|reference_end|>
@article{branco2000noise,
    title={Noise Effects in Fuzzy Modelling Systems},
    author={P. J. Costa Branco, J. A. Dente},
    journal={In: Computational Intelligence and Applications, pp. 103-108,
  World Scientific and Engineering Society Press, Danvers, USA, 1999},
    year={2000},
    archivePrefix={arXiv},
    eprint={cs/0010002},
    primaryClass={cs.NE cs.LG}
}