Sentence examples for mean square percent from inspiring English sources
Furthermore, the predictive ability of the models has been assessed using the root mean square percent error (RMSPE) statistic [30].
On the basis of the correlation coefficient (r) and root mean square percent deviation (e), a fair agreement between theoretically calculated and experimentally observed values is achieved.
The root mean square percent error (RMSPE) statistic [30] is used for Fig. 4: Open image in new window Fig. 4 Summary goodness-of-fit statistic (RMSPE) Open image in new window (15 where x is the variable of interest, N is the number of observations (years) and superscripts 0 and 1 denote observed and fitted measures respectively.
The root mean square percent error (RMSP) was estimated to examine the error between the simulated traffic demand and the actual observed traffic demand, and it was found to be 8.29 %. Figure 8 shows the comparison of observed and simulated point-to-point travel time for the selected route, which has an RMSP value of 2.49 %.
For the simulated gamma spectra considered, burn up was predicted with 0.1% root mean squared percent error (RMSPE) and both cooling time and initial enrichment with approximately 2% RMSPE.
The accuracies of extracting µa and µs' from the measurements were expressed as the root-mean-square percent error (RMSE%) which was calculated as where m was the total number of wavelengths analyzed.
The alternatives were evaluated for selected stand attributes (trees per hectare, basal area per hectare and height to diameter ratio), using root mean square error, absolute percent bias, and mean absolute deviation as criteria.
The root mean square error (and percent bias) ranged from 0.48 mm (13%) to 0.60 mm (22%) for daily (days of satellite overpass) ET and from 7.75 mm (2%) to 13.04 mm (35%) for monthly ET. The spatial and temporal distribution of ET indicates the utility of Landsat 8 for providing important information about ET dynamics across the landscape.
Authors claim that EMD offers better values for a number of noise measures including signal-to-noise ratio (SNR), root mean square error (RMSE), and percent root mean square difference (PRD).
In order to evaluate the performances of the two reconstruction methods, we used the normalized percent mean square error (NPMSE) between the reconstructed signals and the original ones.
We used, as an evaluation criterion, the normalized percent mean square error (NPMSE) between the original signal without noise and the reconstructed signal.
