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Identification of Waste Water Treatment Plant using Neural Networks

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Computational Intelligence Theory and Applications (Fuzzy Days 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1226))

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Abstract

Identification of non-linear processes has always been a problem, as long as the mathematical model structure hardly can be known in advance. In the present paper, conventional Recursive Least Squares estimation is compared with Neural Network identification. Being more flexible and undependable on the model structure, this approach can approximate large variety of relationships. Both strategies are compared identifying a Waste Water Treatment Plant, which posses very strong non-linear properties.

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References

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Author information

Authors and Affiliations

  1. Department of Automation, Higher Institute of Chemical Technology, 1756, Sofia, Bulgaria

    I. I. Voutchkov & K. D. Velev

Authors
  1. I. I. Voutchkov
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  2. K. D. Velev
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Editor information

Bernd Reusch

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© 1997 Springer-Verlag Berlin Heidelberg

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Voutchkov, I.I., Velev, K.D. (1997). Identification of Waste Water Treatment Plant using Neural Networks. In: Reusch, B. (eds) Computational Intelligence Theory and Applications. Fuzzy Days 1997. Lecture Notes in Computer Science, vol 1226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62868-1_140

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  • DOI: https://doi.org/10.1007/3-540-62868-1_140

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62868-2

  • Online ISBN: 978-3-540-69031-3

  • eBook Packages: Springer Book Archive

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