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The fuzzy decision rules are implemented as membership functions (MFs) and the model learns the best fitting parameters of the MFs.
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The best-fitting parameters of the trajectory that explain the arrival times of the shock wave are shown in Table 1.
The best-fitting parameters of morphology priors, the overall substitution rate prior (gamma distribution prior), and the bias prior for two-state characters (beta distribution prior) were estimated using a Markov-chain methodCaslo (MCMC) method alsolso implemented in SIMMAP.
By implementing Masalmeh model, curve fitting was conducted in MATLAB to find out the best fitting parameters with matching experimental values of oil and water relative permeability for the imbibition and drainage, respectively.
After identification of best fitting parameters, all samples were scanned with this protocol.
Simulated and measured velocity event density histograms are compared for fit to choose best fitting parameters.
The experimental data have fitted with the MBrillouin- H - A) model, and the best fitting parameters were analyzed.
We simulated data using our best fitting parameters and compared the results with XCI in both sets of cell lines (Figure 4).
The best fitting parameters according to Gardner et al. (1974) are a = 0.23, and b = 0.25.
Least square minimization was performed to find the best fitting parameters.
Since best fitting parameters are hardly to predict, all combinations were executed.
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