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The method is examined on Iran's North-West Transmission Network, and a mean absolute estimation error of 2.3% and a response time less than 0.1 s are obtained.
The TOA estimation results are shown in Figs. 7, 8, and 9, where the horizontal axis indicates the true TOA t r and the vertical axis gives the mean absolute estimation error.
Particularly, mean absolute estimation error for proposed landmark-aided approach is 6.85°, while those of landmark-aided improved RMPCA without device attitude recalibration, improved RMPCA, landmark-aided RMPCA without device attitude recalibration, and RMPCA are 7.65°, 8.31°, 8.90°, and 9.56°, respectively.
The cross-validation statistics investigated include mean squared estimation error (MSE), root mean squared estimation error (RMSE), mean absolute estimation error (MAE), mean of the root variance of the posterior PDFs (MR), the square of Pearson's correlation coefficient, and the square of Spearman's correlation coefficient.
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Compared with previous landmark-aided RMPCA approach, the proposed approach may reduce the mean absolute heading estimation error by 23.0% (2.05°).
Compared with RMPCA approach, the proposed landmark-aided approach and previous landmark-aided RMPCA approach reduce the mean absolute heading estimation error by 28.3% (2.71°) and 6.9% (0.66°), respectively.
Figure 4 Mean Absolute Error for estimation of the amplitude ratio between components for various SNRs (plain line: MWSM based method; dotted line: Flinn's method).
Figure 3 Mean Absolute Error for estimation of phase shift between components for various SNRs (plain line: MWSM based method; dotted line: Flinn's method).
Figure 3 Relative mean absolute error of IF estimation vs. the order of the TVAR model, M. (a) First component.
Observer performance is shown to be high with a mean absolute final carbon content estimation error for admissible heats equal to 0.0012%.
The mean absolute error in chemists' estimations was around 10%, for some compounds, however, there was a variation of up to 70%.
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