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Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms: Industrial Applications
by Lakhmi C. Jain; N.M. Martin
CRC Press, CRC Press LLC
ISBN: 0849398045 Pub Date: 11/01/98
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6. Conclusions
Most of the systems used for Neural Networks or Fuzzy Logic control use very standard methodologies from the respective literature. It seems that the Neural Networks and Fuzzy Logic literature, and, of course, that for Neuro-Fuzzy, have addressed a variety of issues in system design, stability, and convergence that have not been evaluated extensively in ATM traffic control. With current basic models showing their applicability to the problem at hand, it is time that researchers look for more elaborate models and techniques so that they can propose more efficient, robust, and fast algorithms.
Acknowledgments
The authors would like to thank all their colleagues in the University of Miami and the University of Catania, who provided the results of research projects for this chapter, and IEEE for permission to publish results that appeared in [53] and [54].
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