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Also, it has been observed that they work best when many training vectors are available.
Similar(59)
n is the number of training vectors.
Real time engine diagnostics-prognostics. Relevance training vectors.
The training vectors are centered and normalized according to (9).
The training vectors are generated according to (32).
Its training stage involves simple computations based on the Euclidean distance between the training vectors.
Figure 10 shows the convergence of training trend with such an input training vectors.
Calculate Euclidean distance of test vector to all training vectors that were sampled.
The training of an ANFIS network which involves grade estimation, conducts the input training vectors to target vectors with a minimum total sum of squared error.
Many train lines were simply shut down.
This yields a training vector of 400 dimensions.
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