A Neurofuzzy Learning and its Application to Control system

@inproceedings{Chopra2005ANL,
  title={A Neurofuzzy Learning and its Application to Control system},
  author={Seema Chopra and Ranajit Mitra and I VijayKumar},
  year={2005}
}
A neurofuzzy approach for a given set of input-output training data is proposed in two phases. Firstly, the data set is partitioned automatically into a set of clusters. Then a fuzzy if-then rule is extracted from each cluster to form a fuzzy rule base. Secondly, a fuzzy neural network is constructed accordingly and parameters are tuned to increase the precision of the fuzzy rule base. This network is able to learn and optimize the rule base of a Sugeno like Fuzzy inference system using Hybrid… CONTINUE READING
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References

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