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Exact(19)
In this study, we used MSE (Mean Square Error) as the fitness function which measures average of the square of error.
The objective function is chosen as square of error between the actuated and desired shapes.
Basically, LMS algorithm tries to minimize the energy (or mean square) of error signal, i.e., E[e2] [25].
The F value for each operating parameter is a ratio of the MS to the mean square of error.
Sum square of error (SSE), Chi-square (Χ 2), and the normalized standard deviation (∆q e%), represented by Eqs.
The SS T is sum of square of individual process parameter and sum of square of error as given in Eq. 11.
Similar(41)
Iterative trial and error procedure is used to minimize the sum of square of errors.
In the next step, tuning of EOS parameters is carried out by minimizing square of errors between EOS existing data and experimental data.
The second class includes FLS methods to minimize the total square of errors in the estimated values [15, 16, 31, 48].
In the current study, to evaluate the performance of the neural network training, two criteria of Mean Squared Errors (MSE) and Root Mean Square of Errors (RMSE) are used.
The p-values are based on testing the ratio of mean squares for a factor (like 'mask') and the mean square of errors (random fluctuations), assuming that ratio is F-distributed.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com