Sentence examples for root mean squares error from inspiring English sources

Root mean squares error of prediction (RMSEP) was used for further comparison of the predictability among different constructed models.

The root mean squares error (RMSE) and mean absolute errors were 0.339 and 0.221, respectively, for the validation data set.

The root mean squares error (RMSE) for supercritical carbon dioxide, ethane and trifluoromethane were 0.56, 0.68 and 0.72, respectively.

The root mean squares error of prediction for copper and mercury with and without OSC was 0.010, 0.026 and 0.055, 0.086, respectively.

The root mean squares error of prediction (RMSEP) for uranium determination using PLS and OSC-PLS models were 4.63 and 0.98, respectively.

The root mean squares error of prediction (RMSEP) for acetic acid, monochloroacetic acid and trichloroacetic acid with and without OSC were 0.08, 0.30 and 0.08, and 0.15, 0.40 and 0.18, respectively.

Root mean square error was found out as 1.56.

Genetic Algorithm then searches for the best coefficients by minimizing the root mean square error.

The goodness of fit was evaluated with coefficient of determination and root mean square error.

The trained ANN model generated satisfied root mean square error value.

The root mean square error values are relatively small and ranged between 7 and 9%.