Corpus ID: 17791840

Comparison of Fuzzy Functions with Fuzzy Rule Base Approaches

@inproceedings{Turksen2006ComparisonOF,
  title={Comparison of Fuzzy Functions with Fuzzy Rule Base Approaches},
  author={I. Turksen and A. Çelikyilmaz},
  year={2006}
}
  • I. Turksen, A. Çelikyilmaz
  • Published 2006
  • Mathematics
  • “Fuzzy Functions” are proposed to be determined separately by two regression estimation models: the least squares estimation (LSE), and Support Vector Machines for Regression (SVR), techniques for the development of fuzzy system models. LSE model tries to estimate the fuzzy function parameters linearly in the original space, whereas SVR algorithm maps the data samples into higher dimensional feature space and estimates a linear fuzzy function in the feature space. The membership values of input… CONTINUE READING

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