The use of artificial neural network (ANN) for modeling of the H2O2/UV decoloration process: part I

A brief introduction into artificial neural networks (ANNs) is given, with emphasis on counterpropagation learning strategy, as well as their use for the purpose of modeling and optimization of H2O2/UV decoloration process. The use of Plackett¯Burman partial factorial design for seven variables on three different levels, for the selection of experiments, needed to calculate the significance of variables, is described. Results of learning with Kohonen ANN are described, and the best prediction assembly suggested.