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Radial basis function neural network as predictive process control model

This is an experimental study to compare the performance of the widespread backpropagation network (BP) to the performance of a radial basis function (RBF) and a generalized regression neural network (GRNN) for potential use as on-line process models. Criteria for network comparison include generalization ability to unseen data, robustness to process shifts, performance with sparse training data, and computational demands.