Machine Learning-Based Selection of Efficient Parameters for the Evaluation of Seismically Induced Slope Displacements
Publication: Lifelines 2022
ABSTRACT
Seismically induced slope displacements (D) are often used as a performance index in the seismic design of slope systems. Although previous studies have developed predictive relationships for estimating D, a comprehensive selection of the most efficient parameters to explain D, considering the linearity and nonlinearity in D, has not been thoroughly performed. This study uses modern machine learning-based techniques including Stepwise Selection, LASSO, and Random Forest to identify the influential features in the estimation of D in shallow crustal tectonic settings. The detected influential features are the system’s yield coefficient (ky), initial fundamental period (Ts), earthquake moment magnitude (Mw), peak ground velocity (PGV), and the degraded spectral acceleration at 1.3Ts [Sa(1.3Ts)]. Moreover, the results indicate that there is no significant gain in accuracy beyond five features. The detected significant parameters provide insight and a basis for developing more efficient prediction models.
Get full access to this article
View all available purchase options and get full access to this chapter.
REFERENCES
Berry, W. D., Feldman, S., and Stanley Feldman, D. (1985). Multiple regression in practice (No. 50). Sage.
Blanchet, F. G., Legendre, P., and Borcard, D. (2008). Forward selection of explanatory variables. Ecology, 89(9), 2623–2632.
Bozorgnia, Y., Abrahamson, N. A., Atik, L. A., Ancheta, T. D., Atkinson, G. M., Baker, J. W., Baltay, A., Boore, D. M., Campbell, K. W., Chiou, B. S. J., and Darragh, R. (2014). NGA-West2 research project. Earthquake Spectra, 30(3), 973–987.
Bray, J. D., Macedo, J., and Travasarou, T. (2018). Simplified procedure for estimating seismic slope displacements for subduction zone earthquakes. ASCE Journal of Geotechnical and Geoenvironmental Engineering; 144(3).
Bray, J. D., and Macedo, J. (2019). Procedure for Estimating Shear-Induced Seismic Slope Displacement for Shallow Crustal Earthquakes. ASCE Journal of Geotechnical and Geoenvironmental Engineering; 145(12).
Bray, J. D., and Rathje, E. R. (1998). Earthquake-induced displacements of solid-waste landfills. ASCE Journal of Geotechnical and Geoenvironmental Engineering; 124(3):242–53.
Bray, J. D., and Travasarou, T. (2007). Simplified procedure for estimating earthquake-induced deviatoric slope displacements. ASCE Journal of Geotechnical and Geoenvironmental Engineering; 133(4):381–392.
Candia, G., Macedo, J., and Magna-Verdugo, C. (2018, June). An integrated platform for seismic hazard evaluation. In 11th US National Conference on Earthquake Engineering. Los Angeles, USA.
Candia, G., Macedo, J., Jaimes, M. A., and Magna‐Verdugo, C. (2019). A New State‐of‐the‐Art Platform for Probabilistic and Deterministic Seismic Hazard Assessment. Seismological Research Letters, 90(6), 2262–2275.
Cawley, G. C., Talbot, N. L., and Girolami, M. (2007). Sparse multinomial logistic regression via bayesian l1 regularisation. Advances in neural information processing systems, 19, 209.
Du, W., and Wang, G. (2016). A one-step Newmark displacement model for probabilistic seismic slope displacement hazard analysis. Engineering Geology, 205, 12–23.
Gerath, R., Jakob, M., Mitchell, P., and Van Dine, D. (2010). Guidelines for legislated landslide assessment for proposed residential developments in BC. Association of Professional Engineers and Geoscientists of British Columbia (APEGBC). British Columbia.
Hahs-Vaughn, D. L., and Lomax, R. G. (2020). An introduction to statistical concepts. Routledge.
Hastie, T., Tibshirani, R., and Friedman, J. (2009). The elements of statistical learning: data mining, inference, and prediction. Springer Science and Business Media.
Ho, T. K. (1998). The random subspace method for constructing decision forests. IEEE transactions on pattern analysis and machine intelligence, 20(8), pp.832–844.
ICC (International Code Council). (2015). International Building Code, Washington, DC. International Code Council.
Kavazanjian, E., Wang, J. N., Martin, G., Shamsabadi, A., Lam, I., Dickenson, S. E., Hung, C. J., and Brinckerhoff, P. (2011). LRFD Seismic Analysis and Design of Transportation Geotechnical Features and Structural Foundations-NHI Course No. 130094 Reference Manual Geotechnical Engineering Circular No. 3. United States. Federal Highway Administration.
Krishnapuram, B., Carin, L., Figueiredo, M. A., and Hartemink, A. J. (2005). Sparse multinomial logistic regression: Fast algorithms and generalization bounds. IEEE transactions on pattern analysis and machine intelligence, 27(6), pp.957–968.
Liaw, A., and Wiener, M. (2002). Classification and regression by randomForest. R News, 2(3), 18–22.
Macedo, J. L. (2017). Simplified procedures for estimating earthquake-induced displacements. Ph.D. thesis, Dept. of Civil and Environmental Engineering, Univ. of California, Berkeley.
Macedo, J., Bray, J., and Travasarou, T. (2017). Simplified procedure for estimating seismic slope displacements in subduction zones. In Proc., 16th World Conf. on Earthquake Engineering.
Macedo, J., Candia, G., Lacour, M., and Liu, C. (2020). New developments for the performance-based assessment of seismically-induced slope displacements. Engineering Geology, 277, 105786.
Miller, A. (2002). Subset selection in regression. CRC Press.
Newmark, N. M. (1965). Effects of earthquakes on dams and embankments. Geotechnique; 15(2):139–60.
Olsen, M. J., Ashford, S. A., Mahlingam, R., Sharifi-Mood, M., and Gillins, D. T. (2015). Impacts of potential seismic landslides on lifeline corridors. Oregon. Dept. of Transportation. Research Section.
Rathje, E. M., and Saygili, G. (2008). Probabilistic Seismic Hazard Analysis for the Sliding Displacement of Slopes: Scalar and Vector Approaches. ASCE Journal of Geotechnical and Geoenvironmental Engineering; 134(6), 804–814.
Rennat, E., and Miller, S. (1997). Guía ambiental para la estabilidad de taludes de depósitos de desechos sólidos de mina. Lima: Ministerio de Energía y Minas. Consulta, 10(08), 2019.
Saygili, G., and Rathje, E. M. (2008). Empirical predictive models for earthquake-induced sliding displacements of slopes. ASCE Journal of Geotechnical and Geoenvironmental Engineering; 134(6):790–803.
Soleimani, F., Vidakovic, B., DesRoches, R., and Padgett, J. (2017). Identification of the significant uncertain parameters in the seismic response of irregular bridges. Engineering Structures, 141, 356–372.
Soleimani, F. (2021, August). Analytical seismic performance and sensitivity evaluation of bridges based on random decision forest framework. In Structures (Vol. 32, pp. 329–341). Elsevier.
Tibshirani, R. (2011). Regression shrinkage and selection via the lasso: a retrospective. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 73(3), pp.273–282.
Watson-Lamprey, J., and Abrahamson, N. (2006). Selection of ground motion time series and limits on scaling. Soil Dynamics and Earthquake Engineering, 26(5), 477–482.
Information & Authors
Information
Published In
Lifelines 2022
Pages: 185 - 193
History
Published online: Nov 16, 2022
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.