Sentence examples for mean average error from inspiring English sources

Exact(13)

We achieve a mean average error of 14.89 ± 9.3 µm and 0.096 ± 0.072° for position and orientation learning, respectively.

A modified Chen correlation was developed, which predicted the total heat transfer coefficients with a mean average error of 1.11% and a root-mean-square error of 6.45%.

Because there was no significant surface tension enhancement, the macro-scale Shah (2009) [26] correlation best predicted the data, with a mean average error (MAE) of 20 30% for all geometries.

Using this feature, it calculated a similar performance, RMSE = 0.7 and mean average error 0.5, for 2569 neutral logP, and 8122 pH‐dependent logD7.4, distribution coefficients from the AstraZeneca "in‐house" database.

The accuracy required for the design of new molecules is globally reached: the mean average error is only 19 nm, in spite of the charge-transfer nature of the excitations.

The results obtained from the present model are fairly matches with the simulation results Mori & Nakayama and Schmidt friction factors agree reasonable well with mean average error of 2.2% and 5.7% for R744, respectively.

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Similar(47)

Optimization without symmetry constraints started from the experimental crystal structure of Zr4 sym).[ 13] The relaxed geometry shows mean average errors of 0.01 Å for the bond lengths and 0.53° for the bond angles.

The distributed and centralized fusion methods reduce the mean averaged error of the original signals to 44%and46%6% respectively when using simulated datasets.

Sample characteristics were presented as an average ± mean error.

The proposed framework outperforms state-of-the-art approaches quantitatively and qualitatively with an average head pose mean error of less than 4° in real-time.

For models without age, mean error averaged 0.530 and 0.384 m3 ha−1 yearespectivelyively, for non-parametric and parametric models while for models with age, mean error averaged 0.613 and 0.451 m3 ha−1 yearespectivelyively, for non-parametric and parametric models.

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