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Convergence and comparison studies have been carried out to establish the authenticity and reliability of the solution.
A new algorithm, denoted by RSRR, is presented for solving large-scale nonlinear eigenvalue problems (NEPs) with a focus on improving the robustness and reliability of the solution, which is a challenging task in computational science and engineering.
The numerical results show that the combined PPP has not caused significant impacts on the final solutions, but it greatly improved Position Dilution of Precision (PDOP) and convergence speed and enhanced the reliability of the solution.
The Gibbs tangent plane criterion is of crucial importance to confirm the reliability of the solution obtained for the chemical and phase equilibrium (CPE) problem, and it consequently facilitates the search for the true equilibrium state if a postulated solution is thermodynamically unstable.
The seamless integration of the transformed products will allow the PPP user to have multiple solutions, which will increase the reliability of the solution, for e.g., real-time processing.
The ability to provide multiple solutions would increase the reliability of the solution for, e.g., real-time processing; if there were an outage in the generation of one set of PPP-AR products, the user could instantly switch streams to a different provider.
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Convergence and comparison studies are carried out to establish the reliability of the solutions.
The usage of a modified NSGA-II state-of-the-art multi-objective multi-constraint optimization kernel enables the efficient exploration of design tradeoffs, while the inclusion of corner cases and the usage of the industrial circuit simulators (HSPICE®, Eldo® or Spectre®) ensures the accuracy and reliability of the solutions.
The reliability of the solutions with α not approaching 1 is guaranteed by the theoretical study shown in Section 3.2.
Our goal is to find the end-use solutions that will consume the largest volumes of post-consumer textile waste and this means starting small with experimentation that can inform the ability to scale and determine the reliability of the solutions.
Hence, the problem is still an active field and much remains to be done to improve the reliability of the solutions without increasing the computational cost.
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