Abstract
Mathematical models are normally used to calculate the component concentrations in biological wastewater treatment. However, this work deals with the wastewater from a coke plant and it implies inhibition effects between components which do not permit the use of said mathematical models. Due to this, feed-forward neural networks were used to estimate the ammonium concentration in the effluent stream of the biological plant. The architecture of the neural network is based on previous works in this topic. The methodology consists in performing a group of different sizes of the hidden layer and different subsets of input variables.
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García, H.L., González, I.M. (2006). Ammonium Estimation in a Biological Wastewater Plant Using Feedforward Neural Networks. In: Schwenker, F., Marinai, S. (eds) Artificial Neural Networks in Pattern Recognition. ANNPR 2006. Lecture Notes in Computer Science(), vol 4087. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11829898_12
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DOI: https://doi.org/10.1007/11829898_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37951-5
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