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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.
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Adding the synthetic root volatile dramatically changed this pattern and favored the EPN on the most complex model-roots.
For the simpler models, 5,000 iterations were sufficient for equilibration, while this increased to 20,000 for the most complex models.
The most complex models within the model family can be questioned first for their validity.
FrameWorker returns the most complex models that are common to the input sequences.
Participants with missing data were omitted from the models, resulting in ~4% loss in the most complex models.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com