Prediction of OCR and from PCPT Data Using Tree-Based Data Fusion Techniques
Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 143, Issue 9
Abstract
This study examines the feasibility of using data fusion techniques to predict the overconsolidation ratio (OCR) and undrained shear strength () from piezocone penetration test (PCPT) measurements, in situ stresses, and additional features created from available data. Several data fusion models were developed using two feature-level fusion techniques: regression trees and model trees. Hybrid models were developed using these feature-level fusion techniques and two decision-level fusion techniques, namely, bootstrap aggregation and stacked generalization. After training and testing the data fusion models, the predicted values of OCR and were compared to the reference values, obtained from laboratory or in situ tests, and to the values estimated using several existing interpretation methods. The model trees, which predict continuous values, performed better than the regression trees, which predict discrete values. The decision-level fusion algorithms tended to improve the results of the regression trees, but had little effect on the results of the model trees. Overall, the data fusion models were found to perform well and tended to perform better than the corresponding interpretation methods in estimating values of OCR and .
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The authors appreciate the financial support of the U.S. National Science Foundation under Grant No. CMS-0409594. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the researchers and do not necessarily reflect the views of the funding agencies.
References
Chen, B. S., and Mayne, P. W. (1994). “Profiling the overconsolidation ratio of clays by piezocone tests.”, National Science Foundation, Georgia Institute of Technology, Atlanta.
Chen, B. S. Y., and Mayne, P. W. (1996). “Statistical relationships between piezocone measurements and stress history of clays.” Can. Geotech. J., 33(3), 488–498.
Chen, S. (1994). “Profiling stress history of clays using piezocones with dual pore pressure measurements.” Ph.D. thesis, Georgia Institute of Technology, Atlanta.
Griffin, E. P. (2007). “Interpretation of P/CPT data using data fusion techniques.” M.S. thesis, Univ. of Massachusetts, Lowell, MA.
Gros, X. E. (1997). NDT data fusion, Wiley, New York.
Hall, D. L., and Llinas, J. (1997). “An introduction to multisensor data fusion.” Proc. IEEE, 85(1), 6–23.
Hall, D. L., and McMullen, S. A. H. (2004). Mathematical techniques in multisensor data fusion, 2nd Ed., Artech House, Inc., Boston.
Han, J., and Kamber, M. (2001). Data mining: Concepts and techniques, Morgan Kaufmann Publishers, San Francisco.
Konrad, J.-M., and Law, K. T. (1987). “Undrained shear strength from piezocone tests.” Can. Geotech. J., 24(3), 392–405.
Kurup, P. U. (1993). “Calibration chamber studies of miniature piezocone penetration tests in cohesive soil specimens.” Ph.D. thesis, Louisiana State Univ., Baton Rouge, LA.
Kurup, P. U., and Griffin, E. P. (2009). “Data fusion technique for predicting shear strength and stress history from piezocone penetration tests.” Proc., 17th Int. Conf. on Soil Mechanics and Geotechnical Engineering, IOS Press, Amsterdam, Netherlands.
Larsson, R., and Mulabdic, M. (1991). “Piezocone tests in clay.”, Swedish Geotechnical Institute, Linkoping, Sweden.
Liu, H., Yu, L., and Motoda, H. (2003). “Feature extraction, selection, and construction.” The handbook of data mining, N. Ye, ed., Lawrence Erlbaum Associates, Mahwah, NJ.
Lunne, T., Robertson, P. K., and Powell, J. J. M. (1997). Cone penetration testing in geotechnical practice, Blackie Academic and Professional, London.
Mayne, P. W. (1986). “CPT indexing of in-situ OCR in clays.” Proc., Use of In Situ Tests in Geotechnical Engineering, ASCE, New York, 780–793.
Mayne, P. W. (1988). “Determining OCR in clays from laboratory strength.” J. Geotech. Eng., 76–92.
Mitchell, T. M. (1997). Machine learning, McGraw-Hill, Boston.
Sandven, R. (1990). “Strength and deformation properties of fine grained soils obtained from piezocone tests.” Ph.D. thesis, Norwegian Institute of Technology, Trondheim, Norway.
Wald, L. (2002). Data fusion, definitions and architectures—Fusion of images of different spatial resolutions, Les Presses de l’Ecole des Mines, Paris.
Witten, I. H., and Frank, E. (2005). Data mining: Practical machine learning tools and techniques, 2nd Ed., Morgan Kaufmann Publishers, San Francisco.
Wroth, C. P. (1988). “Penetration testing—A more rigorous approach to interpretation.” Proc., 1st Int. Symp. on Penetration Testing, ISOPT-1, A.A. Balkema, Rotterdam, Netherlands, 303–311.
Information & Authors
Information
Published In
Journal of Geotechnical and Geoenvironmental Engineering
Volume 143 • Issue 9 • September 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Sep 9, 2015
Accepted: Feb 12, 2017
Published online: May 10, 2017
Published in print: Sep 1, 2017
Discussion open until: Oct 10, 2017
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.