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 ?
To choice the best regression tree method, goodness of fit criteria such as coefficient of determination (R2%), adjusted coefficient of determination (Adj-R2%), coefficient of variation (%), SD ratio, relative approximation error (RAE), Root Mean Square Error (RMSE), Pearson correlation between actual and predicted weaning weights were estimated for each combination.
An estimation of the approximation error, as well as the testing of the accuracy of the method by considering distribution of the approximation error for experimentally obtained SHLC, is presented in Section III.
We quantify the algorithm performance by measuring the approximation error, compression ratio, and computation complexity.
i] is neural network approximation error that satisfies [absolute value of ([[epsilon].
2 (Table 2) shows that the basic ensemble approach allows us to obtain an approximation error of magnitude close to the magnitude of uncertainty in the data.
On the other hand, in order to get the same approximation error, the proposed method will require significantly fewer samples than uniform sampling.
i]} - set of adjusting parameters of MCF (the left and right borders of the cut-out interval and approximation error setting e.
Thus, Table 2 shows that a slightly smaller approximation error for this software can be achieved using activation function Inverse Multiquadric and configuration "5-10" or "15-10" (2,4% and 3,0% accordingly), but the training duration is 1618 and 1536 periods against 324 periods in the case of configuration "10-30".
This is also the module responsible for most of the final approximation error as it aggregates data from different processing paths.
Based on the weighted-residual error estimator from [7], we introduced an overall error estimator which controls both, the discretization error as well as the data approximation error (Theorem 3.
It is shown that the approximation error increases as the frequency decreases.
In such a case, the Taylor's theorem ensures that the remainder term e, that is the approximation error given by the difference between the real value attained by the function and its Taylor polynomial, is negligible if compared to the size of [(x - a).