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Please use this identifier to cite or link to this item: http://hdl.handle.net/10651/29094

Title: Simulation of a coke wastewater nitrification process using a feed-forward neuronal net
Author(s): Machón González, Iván José
López García, Hilario
Rodríguez Iglesias, Jesús Avelino
Marañón Maison, María Elena
Vázquez, Isabel
Keywords: Coke wastewater
Activated sludge
Neural network
Ammonium
Thiocyanate
Issue date: 2007
Publisher: Elsevier
Publisher version: http://dx.doi.org/10.1016/j.envsoft.2006.10.001
Citation: Environmental Modelling and Software, 22(9), p. 1382-1387 (2007); doi:10.1016/j.envsoft.2006.10.001
Format extent: p. 1382-1387
Abstract: A laboratory-scale Activated Sludge System (ASS) was employed for the biodegradation of coke wastewater, which contains high concentrations of ammonium, thiocyanate, phenols and other organic compounds. The well-known kinetics models of Monod or Haldane are not very useful due to inhibition phenomena amongst the pollutants and also, they need the determination of a wide range of parameters to be introduced in the models. In this paper, a feed-forward neural network is outlined to obtain a satisfactory approach for estimating the effluent ammonium concentration of the treatment plant
URI: http://hdl.handle.net/10651/29094
ISSN: 1364-8152
Sponsored: The Commission of the European Communities, European Coal and Steel (ECSC). Projects KNOWATER and BIOCONTROL (Ref. Nos. 7210-PR-234 and 7210-PR-235)
Appears in Collections:Artículos
Ingeniería Química y Tecnología del Medio Ambiente

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