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All models indicated good predictions, however, the ANFIS models were more precise compared to the RSM model, which proves that the ANFIS is a powerful tool for modeling and optimizing FAME production in ultrasound reactor.
Why not just sell subscriptions, as in the HBO model, which proves that people are willing to pay for quality?
First, the presented method determines the minimum number of adjoint evaluations for each component as opposed to the brute force-type methods which require full evaluation of all sensitivities for all responses calculated by each component in the overall model, which proves computationally prohibitive for realistic problems.
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There are several safety concerns here about the design: Chasma I was built by the Chinese on their indigenous model which proved to be quite faulty as the original, Qinshan I, developed problems with its water flows.
A new "asymmetric" distortion was found for the GSP model which proved to be comparably stable to the tetragonal structure favored by LDA.
The fibrinolytic activity obtained from the experiments was very close to the actual response predicted by the model, which proved the validity of the model.
The intra- and extracellular inulinase and invertase productions and biomass obtained from experiments were very close to the actual responses predicted by the regression model, which proved the validity of the model.
Optimizing individual applications had average execution times of 1.95 s for RAM models and 21.7 s for ROM models, which proves the efficiency of our approach.
The properties of the CAC method allow to easily deal with region-based models which proves to be hugely advantageous with respect to most previous parametrized approaches, which are only able to deal with edge-based energies.
Over the past decades, research in ML yielded effective theoretical models, which proved successful in several applications such as computer vision [26], data mining [27], and bioinformatics [28].
The CoMSIA steric and electrostatic descriptors were found to be identical with the CoMFA generated models, which proved the consistency of the results.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com