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Network training was performed on the basis of the back error propagation algorithm (Haykin [1999]).
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Some of the Web developers I've spoken with who have walked me through some of the back-end error messages on the site generally agree that system overload is the big problem for those trying to sign up right now.
This grid provides information about the surface of the back at an error level of <0.1 mm [ 16].
The size of the back-propagating prediction errors is determined, in part, by the learning rate, as these errors arise as part of the online learning of new predictions.
A slightly modified error function of the back propagation algorithm resolved this shortcoming and accelerated convergence to a solution.
The internal parameters of the back propagation network, namely, epoch size, error function, learning rate, momentum term, training cycle (Tc), and transfer function are to be appropriately selected to obtain the best network architecture that gives high predictions for the performance variables.
Gonzalez simply continues to struggle passing effectively out of the back and is prone to mental errors.
Considering the dataset of questionable information content, the results were surprisingly good and one of the error back-propagation artificial neural network models has shown the best results.
This adjustment occurs by the iterative propagation of the predictive error back through the entire network with a learning algorithm (for example, the back-propagation algorithm used in the present study).
The network used in this study is a multilayer feed forward neural network with a learning scheme of the back-propagation (BP) of errors and the Levenberg Marquardt algorithm for the adjustment of the connecting weights.
Fig. 7 Frequency of the errors of the back-azimuth estimated from the variable time window.
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