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This increase was not seen in mean relative error.
The Mean Relative Error (MRE) from ANN modeling was less than 0.5%.
A comparison with in situ measurements gave a mean relative error of 23%.
Blind proficiency testing (PT) of spiked soil samples demonstrated a mean relative error of 9.8%.
It is found that GAs outperform RM in terms of mean relative error (MRE).
The robustness and appropriateness of the approach were assessed using the mean relative error (MRE).
The volume fractions were measured with Mean Relative Error (MRE) of less than 1.63%.
The equation satisfies core data with a mean relative error of about 3%.
The results show that the mean relative error of each individual submodel always lies within 10% of the physical measurements, while the complete model has a mean relative error of only 12%.
Five measures were adopted to characterise the error of approximation: coefficient of correlation, mean relative error, RRMSE, EF, and CRM.
The trained network gives the best values over the correlations with less than 4% mean relative error.
More suggestions(15)
mean relative amount
mean residual error
mean relative fluorescence
mean relative difference
mean relative amplitude
mean relative baseline
mean relative impact
mean relative importance
mean relative safety
mean predictive error
mean squared error
mean relative tumour
mean relative tumor
mean relative humidity
mean relative branch
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com