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In this paper, the generalized profile function models, GPFMs, based on linear regression and neural networks, are compared. GPFM provides an approximation of individual models (models of individual stem profile) facility using only two basic measurements. GPFM based on neural network is obtained as the average of all available normalized individual models. It is shown that the application of neural...
The paper presents a further improvement of the adaptive retraining procedure of Artificial Neural Networks (ANNs) used for time series predictions. An important advantage of this approach is that the model is periodically adapted to the changes of the non-stationary environment. The retraining starts from proportionally reduced values of the parameters used in the previous version of the ANN model...
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