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The brief modeling steps are shown in Table 1.

The obtained outputs and the modeling steps are elaborately explained.

Unlike the TSE method, the SD method depends on the type of measurements, since different modeling steps are carried out for TOA and TDOA measurements.

For the interpretation of the results it is most important that all modeling steps are repeated in each bootstrap sample and that the same set of bootstrap samples is used for all strategies.

All modeling steps are processed again on each bootstrap sample to compute correct classification rates and C indexes.

All modeling steps were takien into account for both boosted CARTs and the parametric models and while boosted CARTs may perform worse for the assessment of lower-order interactions for a given sample size, the method's strength lies in the prediction of higher order interactions as well as nonlinear effects.

Appropriate modeling steps were performed with these fuzzy numbers to suggest a fuzzy saturation index.

Local simulated annealing and energy minimization during modeling steps were performed via the Discover module with cvff force field.

Furthermore, the importance of requiring as few batches as possible in the modeling step is considered in the discussion of different models.

For the solution to be automatic and adaptable to different spatial patterns the variogram was automatically fitted; this preliminary modeling step is usually interactive in this interpolation method.

The variability due to the Kriging meta-modeling step is properly taken into account.