article · Journal of Advanced Computational Intelligence and Intelligent Informatics · 1999

Moving Genetic Algorithm Based Fuzzy Modeling

Euntai Kim, Heejin Lee, Changhoon Lee, Junghwan Kim

Cited by 0Open access

Abstract

We propose an approach to Takagi-Sugeno fuzzy modeling via a genetic algorithm consisting of 2 tuning steps - coarse and fine. A moving genetic algorithm (MGA) is proposed and used for fine tuning to obtain robust modeling results. Simulation results demonstrate the algorithm’s validity.

Cite this paper

APA 7

Kim, E., Lee, H., Lee, C., & Kim, J. (1999). Moving Genetic Algorithm Based Fuzzy Modeling. Journal of Advanced Computational Intelligence and Intelligent Informatics, 3(4), 320–325. https://doi.org/10.20965/jaciii.1999.p0320

MLA 9

Kim, Euntai, et al. “Moving Genetic Algorithm Based Fuzzy Modeling.” Journal of Advanced Computational Intelligence and Intelligent Informatics, vol. 3, no. 4, 1999, pp. 320–25, https://doi.org/10.20965/jaciii.1999.p0320.

Chicago

Kim, Euntai, Heejin Lee, Changhoon Lee, and Junghwan Kim. 1999. “Moving Genetic Algorithm Based Fuzzy Modeling.” Journal of Advanced Computational Intelligence and Intelligent Informatics 3 (4): 320–25. https://doi.org/10.20965/jaciii.1999.p0320.

Harvard

Kim, E. et al. (1999) ‘Moving Genetic Algorithm Based Fuzzy Modeling’, Journal of Advanced Computational Intelligence and Intelligent Informatics, 3(4), pp. 320–325. Available at: https://doi.org/10.20965/jaciii.1999.p0320.

BibTeX

@article{kim1999moving,
  title = {{Moving Genetic Algorithm Based Fuzzy Modeling}},
  author = {Kim, Euntai and Lee, Heejin and Lee, Changhoon and Kim, Junghwan},
  journal = {Journal of Advanced Computational Intelligence and Intelligent Informatics},
  volume = {3},
  number = {4},
  pages = {320--325},
  year = {1999},
  doi = {10.20965/jaciii.1999.p0320}
}

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