The training is then restarted using the training samples whose weights are adjusted by the weight ratio.
The ANN performs an iterative process, first using the training data set to calculate the weight and bias estimates, and then applies these parameter estimates in the validation data set to calculate the prediction errors.
In processing mode, learning is switched off by setting ε≡ 0. Instead, previously trained weights are used to generate attentional modulation.
First, in the so-called "training" step, V∗ is determined by minimizing the cross-validation criterion, thereby making use of "training" weights (W^_{ text {train})}(V)) as defined by Eq. (1).
Other strategies include reducing the mass of all items of equipment carried by soldiers [33], using appropriate load carriage training weights [17], including low-impact exercises such as deep water running [61], utilising pre-entry training courses [24, 60] and the introduction of rest weeks during training [8, 40].
In other words, the MLP network is trained using a supervised learning algorithm which uses the training data to adjust the network weights and biases.
And, he added, that is with regular strength-training workouts, using the appropriate weights and with a carefully designed individualized program.
Again, each tool was used individually without any additional information and the voting/consensus model was applied using the weights calculated from the training set (see Table 3).
Findings from these assessments will be used to design a targeted, goal-focused, home-based strength, balance and endurance training regimen using the program Weight Bearing Exercise for Better Balance (WEBB) [ 50].
A parallel structure (similar to an associative memory) with fixed (obtained after training) weights was used to execute the validation stage.
