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Both models are capable of representing watershed responses to current climatic conditions.
Both models are capable of predicting the real efficiency trends of the units.
Both models are capable of representing the experimental data, but the PC-SAFT EoS uses less binary interaction parameters.
Both models are capable of generating spatially correlated synthetic time series for more than one location simultaneously.
Both models are capable of handling variability during the construction process execution and address the complexity of the relations among the production system components, including resource mutual constraints.
Comparisons demonstrate that both models are capable of predicting the turbulent-flow structures at the gap exit which are in a good agreement with measurements.
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The final conclusion was that both models were capable to produce groundwater prospective zones with very good accuracy.
It can be seen that both models were capable to prospect GWPI with very good results, but FR was better in terms of success and prediction rates.
The comparison indicates that, both analyzed models are capable for assessing the quality changes in the dam reservoir; however, they are different in terms of the accuracy of short- and long-term results (Mark et al. 2001).
We also found that both NN and LR models are capable of capturing the ionospheric foF2 responses during two great geomagnetic storms (28 October–1 November 2003 and 6 12 November 2004) which have been demonstrated to be difficult storms to model in previous studies.
It can be seen that both gene conversion models are capable of generating simulated CMT1A-REP datasets that are not significantly different from the observed alignment.
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