This paper aims the treatment of leachate in a reactor in batches using the advanced oxidation process via Fenton, allowing partially oxidize organic compounds and making them biodegradable, being removed by filtration or sub-2 Diovana Aparecida dos Santos Napoleão et al.sequent biological treatment. This technique allows to verify the satisfactory operating conditions for greater removal efficiency of both organic load as nutrients. The process was modeled via neural network of the kind feedforward and backpropagation. The best configuration to represent the relationship between the variation in chemical oxygen demand (network output layer) and the factors presence or absence of lime, time, pH, volume of hydrogen peroxide solution and concentration of Fe 2+ (network input layer) was obtained with 12 neurons in the hidden layer and the tangent sigmoidal transfer functions. The correlation coefficients above 0.99 for the phases of training and simulation show the power of the generalization of neural model obtained.
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