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Further research is needed to fully explore the potential applications of the proposed method and validate it.
Therefore, it needs to perform the calculations based on the Gibbs free energy minimization method and validate the data through experimental means.
Finally, a real-world case study in Taiwan was used to explain the research process of the GQFD method and validate the practicality of the proposed method.
We propose a nonlinear elastic impedance inversion method based on a fast Markov chain Monte Carlo (MCMC) method, and validate the feasibility and robustness of the method by testing the noise immunity of well data.
The results from this category confirm the reliability of our method and validate our proposed model.
Here, we describe the AGEP method and validate its utility in the analysis of microarray data from normal and disease tissue types as well as the quantitative analysis of cell differentiation patterns.
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We elaborated on the foundations of our numerical method and validated it on assorted test cases.
The paper illustrates the method and validates the method through analytical analysis and through simulation of real and synthetic data.
The model was solved numerically by using finite difference method and validated against experimental data.
In Study 1, a complete list of factors was generated using a focus group method and validated on a broader sample using a survey method with network professionals.
The present model is solved with the finite element method and validated with experimental and numerical results from literature.
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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