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While increasing complexity from the simplest to the more complex model leads to lower uncertainty bounds and more reliable values of the lysimeter discharge at monthly and seasonal time scales, uncertainty bounds became larger when complexity increased in the most complex model.
The most complex model derived (N P model) accounts for chemical reaction reversibility and the Nernst Planck effect created by ionic species and is solved numerically.
The most complex model included over 4500 reactions and tracked 93 polymeric and low molecular weight species, both dead and live species.
Results revealed that the most complex model structure may not necessarily be the most effective in simulating the dynamics of total phosphorus (TP) concentrations in the wetland.
Although the most complex model reproduced the field observations best, the marginal improvement in model performance compared to simpler models was outweighed by the higher costs of increased complexity.
However, it is also the most complex model because of the many unknowns to estimate.
The most complex model structure generally shows a higher sensitivity of parameters.
Even the most complex model of polydisperse multishaped particles could not fit the whole scope of the observational data no matter what refractive index was tried.
This might be explained by that the multilevel testlet model is the most complex model, and estimation problems can occur, such as unconverged or extreme solutions.
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Adding the synthetic root volatile dramatically changed this pattern and favored the EPN on the most complex model-roots.
He was surprised to learn that astronomers cannot actually confirm the accuracy of their most complex models.
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