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After the training of each subnet, the weighted factor ω can also be obtained.
Training of each neuro-fuzzy sub-component in ensemble network is carried out using a hybrid learning scheme.
Training of each MLP network for the DOHANN model has required less computer time in comparison to SNN model.
After the training of each subnet, the optimal weighted factor ω can be obtained via least square algorithm.
After discussion among the authors, we felt that the years of training of each group, as described, were equivalent.
Prior to the training of each network, the program randomly divided the training set into a validation set and a reduced training set with approximately the same size.
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Emails were sent indirectly to all trainees in our cohort; the Heads of Training for each of the 16 UK training deaneries (geographical division of UK training schemes) were contacted and asked to forward our email.
The minimum of training for each of the five categories was 5 min.
The number of trains of each type passing by on a certain track section determine the average roughness.
We use different video episodes for the test and train of each experiment.
The fitness (i.e., total delay of the trains) of each solution has been evaluated by a simulation of train traffic flow known to be CA method.
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