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The Back-propagation Neural Network (BPN), Probability Neural Network (PNN), other algorithms, and the proposed ERBFN were all developed and compared to check the performance.
In this section, the results obtained by MATLAB and CMG-IMEX simulator had been compared to check the perfection of the developed new dual-porosity model (Fig. 22).
Short acquisition time spectra were recorded before and after each experiment and compared, to check the non-degradation of the samples under the X-ray beam.
The transport studies of the newly synthesized membrane have been carried out using various methods suggested by different research groups [8, 9, 10] and the fixed charge density values have been compared to check the applicability of the theories to the membrane system.
The results were then compared to check the percentage of cases with identical classifications.
Estimated parameters of mutational bias and selection coefficients between the FMutSel-M0 and the FMutSel-M3 model were compared to check the consistency of the likelihood estimation.
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The tree topologies from the six independent runs were also compared to check whether the runs were converging on the same topology.
Both distances are then compared to check whether the MS is moving toward (in both x and y axis) or away APn, illustrating the second for iteration in Algorithm 3. If the MS is moving toward APn then the APR is utilized and if it is moving away, the APR is discarded.
Imputed and original values were compared to check that the imputation process had produced no anomalies.
Both results of analysis will be compared to check whether the results are consistent.
Baseline data from the control and intervention groups will be compared to check for comparability of the groups.
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