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The roots mean squared error, coefficient of determination, and the predicted value were used to determine the fitness of the model.
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Values of root mean square error of calibration and prediction, and normalized root mean squared error were used as criteria to define the best calibration condition.
Finally, the root mean squared error (RMSE) is calculated from the square root of MSE.
root mean squared error of prediction.
RMSE root mean squared error, MAE mean absolute error.
The root mean squared error (RMSE) is evaluated by.
Figure 5 The root mean squared error of timing estimator.
The root mean squared error of calibration (RMSEC) is 0.0503 and the root mean squared error of validation (RMSEV) is 0.0485.
Root mean squared error and correlation coefficient were evaluated as performance criteria.
In the former the root mean squared error of prediction (RMSEP) was 0.42 0.50% SOC.
The root mean squared error was 0.03 mm, which is the effective precision of the method.
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