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Filling-in models were successful in predicting psychophysical data for brightness perception.
Both the FB and CPFD models were successful in resolving key issues in 3-D, whereas 2-D models tended to seriously underpredict particle volume fraction, especially near the wall.
These models were successful (R2 ≥ 0.89) for sand, clay, pH, total C and N, exchangeable Ca, Mg and effective CEC; but not for silt, available P and exchangeable K and Al (R2 ≤ 0.82).
Although both PLSR and RF models were successful in modelling C fractions, RF models appear to target the physical properties linked to the property being analysed, and may therefore be the better modelling method to use when generalising to new areas.
As with the supported employment findings of the 1990s, Cook et al. (2005) continued to find that supported employment models were successful in promoting better employment and earnings outcomes for people with psychiatric impairments.
All existing models were successful in illustrating different aspects of CPG function while (necessarily) neglecting others.
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Crop models are successful in predicting the impact of environmental changes on crop productivity.
All models are successful in dealing with the problem of autocorrelation.
On the other hand, it is by no means clear that these connectionist models are successful and generalizable (scalable).
But as technology replaced workers and consumers became increasingly disillusioned with modern business models, being successful became more about pivoting in the direction markets are facing.
This study has shown that the response surface methodology (RSM) and adaptive neuro-fuzzy inference system (ANFIS) models are successful tools to predict the polymer solution viscosity.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com