Genetically Optimized Hybrid Fuzzy Neural Networks Based on Simplified Fuzzy Inference Rules and Polynomial Neurons

Sung-Kwun Oh, Byoung-Jun Park, Witold Pedrycz, Tae-Chon Ahn. Genetically Optimized Hybrid Fuzzy Neural Networks Based on Simplified Fuzzy Inference Rules and Polynomial Neurons. In Vaidy S. Sunderam, G. Dick van Albada, Peter M. A. Sloot, Jack Dongarra, editors, Computational Science - ICCS 2005, 5th International Conference, Atlanta, GA, USA, May 22-25, 2005, Proceedings, Part I. Volume 3514 of Lecture Notes in Computer Science, pages 798-803, Springer, 2005. [doi]

@inproceedings{OhPPA05:0,
  title = {Genetically Optimized Hybrid Fuzzy Neural Networks Based on Simplified Fuzzy Inference Rules and Polynomial Neurons},
  author = {Sung-Kwun Oh and Byoung-Jun Park and Witold Pedrycz and Tae-Chon Ahn},
  year = {2005},
  doi = {10.1007/11428831_99},
  url = {http://dx.doi.org/10.1007/11428831_99},
  tags = {optimization, rule-based, rules},
  researchr = {https://researchr.org/publication/OhPPA05%3A0},
  cites = {0},
  citedby = {0},
  pages = {798-803},
  booktitle = {Computational Science - ICCS 2005, 5th International Conference, Atlanta, GA, USA, May 22-25, 2005, Proceedings, Part I},
  editor = {Vaidy S. Sunderam and G. Dick van Albada and Peter M. A. Sloot and Jack Dongarra},
  volume = {3514},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {3-540-26032-3},
}