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The authors would like to thank Lorenzo Stella of the Microsoft Research - University oforrento Computaionalomputandnal and Systems Biology of Trento (Italy) for his valuable suggestions and for his collaboration in testing the method and validating the results and Sanders Veltkamp of the Astellas Pharma for his help in understanding the experimental obsevation and the pharmacokinetic model.
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Further research is needed to fully explore the potential applications of the proposed method and validate it.
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.
Therefore, it needs to perform the calculations based on the Gibbs free energy minimization method and validate the data through experimental means.
The proposed model is solved numerically based on a finite volume method and validated with experimental data.
Accurate, time saving and memory space saving models are developed with a new numerical method and validated with finite element method and boundary element method.
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.
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