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Hebbian learning rule is used for network training.
Input and output variables from CCD were used for network training, verification and testing.
In this context RBFN architecture is selected, because it is able to cope with 'new fault' conditions not well represented in the fault dictionary used for network training.
The Levenberg Marquardt back-propagation algorithm was used for network training.
We performed 11 experiments, in each of which one student's data was held out for testing, and the other ten students' data were used for network training.
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Finally, experimental data are used for neural network training and validation.
The HS equation calibrated by applying the same data used for neural network training.
A 38-3 factoriall factorial experimental design is conducted to efficiently collect structured data used for neural network training and testing.
Ninety-two data points were used for the network training, model validation and testing in a 2 1 1 relative proportion.
The first 800 samples were used for RBF network training.
Finally, the algorithm used for the network training affects its performance and effectiveness.
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