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However, our evaluation selected weight values empirically.
In order to obtain the optimal combined index weights, the two weights are normalized by a selected weight factor.
By estimation of the output error and application of the back-propagation process (to the system), the selected weight in model was modified.
Although the selected weight function may not have been the best one among all possible weights, it was the best approximation found.
Finally, the multi-objectives are integrated into a single objective function: f = a_{1} f_{text{b}} + a_{2} f_{text{c}} - a_{3} f_{text{t}}, (6 where positive numbers a1, a2, a3 are appropriately selected weight coefficients.
We review the so-called nonstandard mixed sensitivity problem, which introduces an integrator to a selected weight, as well as the linear classical disturbance suppression problem and the linear H∞ disturbance suppression problem.
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Both reference and examined text documents were represented by the vector of 5,210 key phrases weighted according to the selected weighting scheme, described in the Section 3.5, so they could be compared.
The selected weights for the non-linearity were heuristic, and automatic selection of optimal weights from the evaluation data is desirable.
The selected weights and biases are normally updated using an iterative process.
Hence, it warranted several runs and trial runs in each selected weights.
The selected weighting factor is in accordance with this observation, providing more weight to the left periocular region.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com