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We use third-order interpolation (cubic polynomial fitting) as optimal fitting condition [4].
Our aims in the proposed approach are to formulate an appropriate objective function for the optimal fitting of a set of fracture planes to the micro-seismic data and to derive an efficient modification scheme to update the model parameters.
Using the general fitting model (Equations 1 and 2) and defining the optimization criterion, the optimal fitting coefficients can be obtained and broadcast to the users.
Different optimization aspects and architecture optimal fitting are presented.
The optimal layer stacking pattern is determined by a fitting function that applies temperature difference between plates under abnormal and design conditions.
The set of the fitting coefficients meeting the optimization criterion is determined as the optimal fitting coefficients for local troposphere modeling.
A set of local troposphere fitting coefficients are then derived using a proposed optimal fitting model.
Generally, The Sigmoidal fitting function was found to be the most accurate fitting function.
An optimal fitting is obtained through a series of statistical tests between successive fittings and the histogram tails.
The model smoothes pixels within regions and enhances pixels at boundaries by creating a fitting function.
Next, we project the fitting function over a structured lattice, obtaining a 'regularized' polyhedral surface.
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