Novel Self-Organizing Takagi Sugeno Kang Fuzzy Neural Networks Based on ART-like Clustering

@article{Wang2004NovelST,
  title={Novel Self-Organizing Takagi Sugeno Kang Fuzzy Neural Networks Based on ART-like Clustering},
  author={Di Wang and Hiok Chai Quek and Geok See Ng},
  journal={Neural Processing Letters},
  year={2004},
  volume={20},
  pages={39-51}
}
The existing Self-Organizing Takagi Sugeno Kang Fuzzy Neural Networks (S-TSKfnn) structure uses virus infection clustering (VIC) method to generate fuzzy rules. In this paper, we propose a novel architecture called Modified S-TSKfnn (MS-TSKfnn) that uses ART-like clustering called discrete incremental clustering (DIC). By doing so, MS-TSKfnn is able to handle online data input, and its performance is also enhanced. Most importantly, the accurate clustering in the fuzzy set derivation has… CONTINUE READING
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