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Neuro-fuzzy control using self-organizing neural nets

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2 Author(s)
Zia, F. ; Dept. of Electr. & Comput. Eng., Syracuse Univ., NY, USA ; Isik, C.

This paper discusses a new approach to design a fuzzy logic control system, based on the self-organizing map (SOM) neural network. SOM is used to generate multivariate fuzzy state space from system's input-output data through unsupervised training. The trained SOM is then used as a part of an inference mechanism for a fuzzy logic controller. The proposed method is compared with other fuzzy neural network approaches. Sample data from a chemical plant is used to demonstrate the technique

Published in:

Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the Third IEEE Conference on

Date of Conference:

26-29 Jun 1994

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