An incremental construction learning algorithm for identification of T-S Fuzzy Systems

@article{Wang2008AnIC,
  title={An incremental construction learning algorithm for identification of T-S Fuzzy Systems},
  author={Di Wang and Xiao-Jun Zeng and John A. Keane},
  journal={2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence)},
  year={2008},
  pages={1660-1666}
}
This paper proposes an incremental construction learning algorithm for identification of T-S fuzzy Systems. The mechanism of the algorithm is that it is an error-reducing driven learning method. Beginning with a simplest T-S fuzzy system, the algorithm develops the system structure by adding more fuzzy terms and rules to reduce the model errors in a dasiagreedypsila way. The main features of the proposed algorithm are that, firstly, it can automatically determines and controls the number and… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-10 of 17 references

A new approach to fuzzy modeling ”

M. Park E. Kim, S. Ji, M. Park
IEEE Trans . Syst . Man and Cybern . - A • 2006

Simpl_eTS: a simplified method for learning evolving Takagi-Sugeno fuzzy models

The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05. • 2005

An Approach for On - line Extraction of Fuzzy Rules using a Sefl - organising Fuzzy Neural Network "

T. M. McGinnity, G. Prasad
IEEE Transactions On Fuzzy Systems • 2002