On-line learning, reasoning, rule extraction and aggregation in locally optimized evolving fuzzy neural networks

@article{Kasabov2001OnlineLR,
  title={On-line learning, reasoning, rule extraction and aggregation in locally optimized evolving fuzzy neural networks},
  author={Nikola K. Kasabov},
  journal={Neurocomputing},
  year={2001},
  volume={41},
  pages={25-45}
}
A fuzzy neural networks are connectionist systems that facilitate learning from data, reasoning over fuzzy rules, rule insertion, rule extraction, and rule adaptation. The concept of a particular class of fuzzy neural networks, called FuNNs, is further developed in this paper to a new concept of evolving neuro-fuzzy systems (EFuNNs), with respective algorithms for learning, aggregation, rule insertion, rule extraction. EFuNNs operate in an on-line mode and learn incrementally through locally… CONTINUE READING
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