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The NRTL-DVIS model shows better accuracy than other models proposed in the literature.
The adapted model shows better whisper recognition results than the neutral model.
Furthermore, the Stefan model shows better agreement with the experimental results than the Single-phase model.
What's more, the model shows better ability in recovering long-distance dependencies compared with common neural network models.
It has been found that the analyzed forecast model shows better results than those obtained using an autoregressive model.
However, when the concentration of BN dopants is increased from two atom to four atom the endo doping model shows better performance than other two models.
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The current UMC2013 model showed better performance than the previous model of Iwata et al. (2008).
Hence, our model showed better performance in the large field optimization.
Receptor based MFA model showed better results when compared with least squares and pharmacophore based models.
In the MBPPSA model, vegetables with higher k values (the constant of the model) showed better potential in methane production.
It is noted that the P2D-based model showed better execution time than the SPD-based model.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com