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A three-layer feed-forward neural network was used for the prediction of the polarity/polarizability parameter π 2 H . A simulated annealing algorithm was used to minimize the error at the neural network output. Descriptors related to the structure of the compounds were calculated as the input vector. The Kohonen neural network was used to split the data set into training and testing sets. The results obtained from the neural network were compared with the MLRA results.doi:10.1021/ci960347e fatcat:fjjfpic6wjamvisakfxtwq25qm