Sentence examples for high relative errors from inspiring English sources

For example, the proton NMR method yielded hydrogen contents of 1.51 wt% for 1,2,4-trichlorobenzene, 2.55 wt% for 1,2-dichlorobenzene, and 3.90 wt% for furfuraldehyde compared to the theoretical values of 1.67, 2.74, and 4.20 wt%, respectively, giving high relative errors.

The results reveal high relative errors; the mean value of the estimated parameters are overall far from the reference ones.

Note that these high relative errors for low absolute values could at least partly result from manual extraction of the data points from Figure 3 in [ 59].

These are manifested by high relative errors of the reconstructed parameter values, spread uniform-like distributions of some parameter estimates, and strong correlations between some pairs of estimated parameters.

This section presents simulation results with an error standard deviation of 10 m in a 100×100 m area, to study each estimators' performance in a high relative error percentage condition, i.e., P e >14%.

The Fr predicted by ANFIS and the input combination of Model 3 that employed R/D as a transport mode parameter led to a decrease in relative error by 3% compared with Model 2. Hence, the Fr value had high relative error and was underestimated.

One is they have high relative error (low signal-to-noise ratio).

It becomes obvious from the scattering of data points in Fig. 10a that the value of 0.2 eV has a high relative error and should more be taken as indication of very little activation than as an exact value.

These estimates usually converge faster for the dominant elements, with higher relative errors for the less important ones, which naturally lends to finding the former quicker.

The only regions resulting in higher relative errors are those corresponding to small organs presenting a large variability among mice such as the testicles, bladder, kidneys and pancreas.

Note that, in the fits of the data from the cca1/lhy mutant plants for the early and the normal night, we did not consider the two data points closest in time to 24 hr from the datasets, as they are characterized by very low values of starch content and, therefore, are likely to be affected by higher relative errors compared to the other data points.