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Modelling of air pollution parameters, according to the meteorological data is a necessary for preventing the repetition of same problems. During recent years, neural network-based models have been shown to be powerful tools in the simulation of variations in air quality and provide better alternative to statistical models because of their computational efficiency and generalization ability. In this study, prediction of future daily SO2 concentrations in Konya (Turkey) using MLP (Multilayer Perceptron) artificial ...