Assessment of coagulation pretreatment of leachate by response surface methodology.

Coagulation-flocculation is a relatively simple technique that can be used successfully for the treatment of old leachate by poly-aluminum chloride (PAC). The main objectives of this study are to design the experiments, build models and optimize the operating parameters, dosage m and pH, using the central composite design and response surface method. Developed for chemical organic matter (COD) and turbidity responses, the quadratic polynomial model is suitable for prediction within the range of simulated variables as it showed that the optimum conditions were m of 5.

Knowledge extraction from a nitrification denitrification wastewater treatment plant using SOM-NG algorithm.

SOM-NG is a hybrid algorithm that is able to carry out visualization of process data, nonlinear function approximation, classification and clustering. The supervised version of SOM-NG produces a new type of 2D lattices called gradient planes which are useful to determine the dynamics of a target variable according to the remaining training variables. In this way, it is an interesting tool for data mining in order to extract knowledge from databases for nonlinear systems.

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

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).