absolute error


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absolute error

[′ab·sə‚lüt ′er·ər]
(mathematics)
In an approximate number, the numerical difference between the number and a number considered exact.
(ordnance)
Shortest distance between the center of impact or the center of burst of a group of shots and the point of impact or burst of a single shot within the group.
Error of a sight consisting of its error in relation to a master service sight with which it is tested and of the known error of the master service sight.
References in periodicals archive ?
AccuWeather ranked first in the categories ForecastWatch uses to measure accuracy of temperature forecast, including mean absolute error, percentage of forecasts within three degrees Fahrenheit, and percentage of forecasts with no error.
The results were compelling: the mean wind speed absolute error observed between the SLD and the met mast reference was less than 0.
For example, the average absolute error for the total population projection for South Australia is lower than those at every age group in Figure 2 due to the mix of positive and negative age-specific errors which partially offset one another when summed over all ages.
The mean absolute error for both of the NIESR forecasts is smaller than their analogous random walk counterparts, highlighting that the NISER forecasts are closer to the first outturn than the relevant random walk forecasts.
This figure is an average of overestimates and underestimates; the absolute error is even higher.
1 displays the average and worst absolute error in finding eigenvalues for Sturm bisection as compared to the Matlab eigenvalues, which are considered the exact ones.
Integral Square Error (ISE), Integral Time Square Error (ITSE) and Integral Time Absolute Error (ITAE) cost functions are used for the purpose of optimizing conventional controller gain value of the AGC system.
Different models can be compared using criteria such as the Akaike's Information Criterion (AIC) or Schwarz's Bayesian Criterion (SBC) and RSquare, where larger values indicate a better fit and Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) where smaller values indicate a better fit (Figure 3).
The model has a similar absolute error of predicted vote shares across all candidates ([mu] = 8.
absolute error, and subsequently selects the better parse trees for reproduction and variation to form a new population.
11] Table 4: Computed values of absolute error = [absolute value of y(t) - y] for Example 4.
First we compute Mean Absolute Error (MAE) and Root-Mean Squared Error (RMSE) as follows: