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A coordinate system was designed to normalize the effects of applied variables and material properties.
Among GP applications, pile length, pile diameter, and undrained shear strength at pile tip were the most applied variables.
Afterward, a detailed review of the previous studies on pile foundations was conducted and a list of applied variables as well as their usage frequencies were presented.
Comparing this number with 38 applied variables in ANN applications shows that further studies are needed to explore more variables in GP.
The applied variables predicted carbon release well (i.e. 95% of the carbon loss was predicted) and notably both the non-equilibrium and equilibrium phases of erosion was predicted.
In hammer/SPT/CPT information category, hammer weight, hammer drop height, driving energy delivered to the pile, and average SPT Along the pile shaft had similar repeat percentage of 16% and were the highest applied variables as an input of ANN models (Fig. 5c).
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Each variable is chosen with a probability p c and the above SBX operator is applied variable-by-variable.
Very good correlation is observed between the prediction and the wear depth, independently of the applied variable amplitude sequences.
Figure 5a shows that, between all parameters related to pile properties, the pile length with 31% repeat rate, was the most applied variable.
To identify the genes and SNPs predominantly responsible for the pathway effect, we applied variable selection and model fitting on all the SNPs within associated pathways, within the framework of 10-fold CV.
The applied variable is constructed on the basis of the work of Juhl et al [ 58].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com