Axial capacity prediction for driven piles using ANN: model comparison
TMH Lok, WF Che - Geotechnical engineering for transportation …, 2004 - ascelibrary.org
A comparison of three different models using back-propagation neural network for
estimation of pile bearing capacity from dynamic stress wave data was made. The bearing
capacity predicted by TNOWAVE was employed as the desired output in training. The study
shows that the neural network models generally predict total bearing capacity more
favorably if both the stress wave data and the properties of the driven pile are considered as
the input parameters. In addition, better selection of input parameters rather than the …
estimation of pile bearing capacity from dynamic stress wave data was made. The bearing
capacity predicted by TNOWAVE was employed as the desired output in training. The study
shows that the neural network models generally predict total bearing capacity more
favorably if both the stress wave data and the properties of the driven pile are considered as
the input parameters. In addition, better selection of input parameters rather than the …
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