Comparing feed-forward versus neural gas as estimators: application to coke wastewater treatment

• Published in: Environmental technology Vol. 34; no. 9; pp. 1131 - 1140
• Main Authors: Machón-González, Iván, López-García, Hilario, Rodríguez-Iglesias, Jesús, Marañón-Maison, Elena, Castrillón-Peláez, Leonor, Fernández-Nava, Yolanda
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 01.05.2013; Taylor & Francis Ltd
• Subjects: activated sludge; Applied sciences; Bacteria; Bacteria - metabolism; Bioreactors; Carbon; Coke; coke wastewater; Denitrification; denitrifying bacteria; environmental technology; Exact sciences and technology; feed-forward; Gases; General purification processes; Instability; methanol; Methyl alcohol; model validation; Models, Theoretical; Networks; neural gas; neural network; Neural networks; Neural Networks (Computer); nitrate; nitrates; Nitrates - analysis; Nitrates - metabolism; Pollution; Sewage; Stability; Studies; Waste Disposal, Fluid - methods; Waste water; Waste Water - chemistry; wastewater; wastewater treatment; Wastewaters; Water treatment and pollution; British Isles; Activated sludge; Stability; coke wastewater; Nitrates; Neural network; nitrate; Modeling; Waste water; Biological purification; Industrial waste water; Denitrification; Bacteria; Instability; feed-forward; Robustness; Waste water purification; neural gas
• ISSN: 1479-487X; 0959-3330; 1479-487X
• DOI: 10.1080/09593330.2012.737863

Numerous papers related to the estimation of wastewater parameters have used artificial neural networks. Although successful results have been reported, different problems have arisen such as overtraining, local minima and model instability. In this paper, two types of neural networks, feed-forward and neural gas, are trained to obtain a model that estimates the values of nitrates in the effluent stream of a three-step activated sludge system (two oxic and one anoxic). Placing the denitrification (anoxic) step at the head of the process can force denitrifying bacteria to use internal organic carbon. However, methanol has to be added to achieve high denitrification efficiencies in some industrial wastewaters. The aim of this paper is to compare the two networks in addition to suggesting a methodology to validate the models. The influence of the neighbourhood radius is important in the neural gas approach and must be selected correctly. Neural gas performs well due to its cooperation–competition procedure, with no problems of stability or overfitting arising in the experimental results. The neural gas model is also interesting for use as a direct plant model because of its robustness and deterministic behaviour.