A hybrid learning method composed by the orthogonal least-squares and the back-propagation learning algorithms for interval A2-C1 type-1 non-singleton type-2 TSK fuzzy logic systems

@article{MaradelosAngelesHernandez2015AHL,
  title={A hybrid learning method composed by the orthogonal least-squares and the back-propagation learning algorithms for interval A2-C1 type-1 non-singleton type-2 TSK fuzzy logic systems},
  author={M. de los Angeles Hernandez Mar{\'i}adelosAngelesHernandez and Patricia Melin and Gerardo M. Mendez and Oscar Castillo and Ismael Lopez-Juarez},
  journal={Soft Comput.},
  year={2015},
  volume={19},
  pages={661-678}
}
The purpose of this paper is to present a hybrid learning method for interval A2-C1 type-1 non-singleton type-2 TSK fuzzy logic system that uses the recursive orthogonal least-squares algorithm to tune the type-1 consequent parameters, and the back-propagation algorithm to tune the interval type-2 antecedent parameters. Based on the combination of these two training algorithms the new hybrid learning method changes the interval type-2 fuzzy model parameters adaptively and minimizes the proposed… CONTINUE READING
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Modeling and control of the coiling temperature using type-2 fuzzy logic systems

  • GM Mendez, L Leduc-Lezama, R Colas, G Murillo-Perez, J RamirezCuellar, JJ Lopez
  • Ironmak Steelmak
  • 2010
Highly Influential
12 Excerpts

Temas de Identificación y Control Adaptable

  • A Aguado
  • La Habana,
  • 2000
Highly Influential
6 Excerpts

A nonlinear voltage controller based on interval type 2 fuzzy logic control system for multimachine power system

  • A Abbadi, L Nezli, D Boukhetala
  • Electr Power Energy Syst
  • 2013
2 Excerpts

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