1754
Proceedings of the 18
th
International Conference on Soil Mechanics and Geotechnical Engineering, Paris 2013
Figure 3. Comparison between the measured and predicted
ROP from the ANN model.
Figure 4. Comparison between the measured and predicted
ROP from the SVM model.
6 CONCLUSIONS
Using a database of geotechnical data published by Yagiz
(2008) ANN and SVM algorithms were applied in order to
develop new models to predict the machine performance.
In the training phases, using a cross-validation scheme, the
SVM algorithm had slightly better performances than the ANN
algorithm. However, using the induced model with all dataset,
the ANN gives lower errors and greater R than SVM.
When all the dataset is used ANN had even better
performance than the models presented by Yagiz (2008) and
Yagiz and Karahan (2011).
The most important input variable is PSI and the less
important input one is UCS.
7 ACKNOWLEDGEMENTS
This study was financed by the Portuguese Foundation for
Science and Technology - PEst-OE/ECI/UI4047/2011.
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