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The mean square errors (MSEs) of frequency estimates are calculated.
So as to minimize The sum of square errors (SQE).
The mean square errors are calculated as follows: (16).
The minimum mean square errors of 0.17 and 19.58, and the minimum root mean square errors of 0.41 and 4.42 for SSeff and CODeff could also be achieved.
Experimental results have shown the performances of visual synthesis methods by root mean square errors.
The root mean square errors of the observed and predicted values are less than 8%.
The relative root mean square errors of the model for growth ranged between 0.09 and 0.31.
The algorithm returns simulated normalized root mean square errors systematically smaller than 5% in 10 s.
Similar(3)
The root-mean-square errors of predictions (RMSEPs) were between 0.48 and 1.37 ng ml−1.
And the root-mean-square errors are also computed and listed in Table 13.
Figure 7 displays root-mean-square errors (RMSE) obtained by each iteration of hybrid TLBOFIS.
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