An alternative approach to the ground motion prediction problem by a non-parametric adaptive regression method

References

• Akkar, S., and J. J. Bommer. 2006. “Influence of Long-Period Filter Cut-Off on Elastic Spectral Displacements.” Earthquake Engineering and Structural Dynamics 35 (9): 1145–1165. doi: 10.1002/eqe.577
   Web of Science ®Google Scholar
• Akkar, S., and J. J. Bommer. 2010. “Empirical Equations for the Prediction of PGA, PGV and Spectral Accelerations in Europe, the Mediterranean Region and the Middle East.” Seismological Research Letters 81 (2): 195–206. doi: 10.1785/gssrl.81.2.195
   Web of Science ®Google Scholar
• Akkar, S., and Z. Çağnan. 2010. “A Local Ground-Motion Predictive Model for Turkey, and Its Comparison with Other Regional and Global Ground-Motion Models.” Bulletin of the Seismological Society of America 100 (6): 2978–2995. doi: 10.1785/0120090367
   Web of Science ®Google Scholar
• Akkar, S., Z. Çağnan, E. Yenier, O. Erdoğan, M. A. Sandıkkaya, and P. Gülkan. 2010. “The Recently Compiled Turkish Strong Motion Database: Preliminary Investigation for Seismological Parameters.” Journal of Seismology 14 (3): 457–479. doi: 10.1007/s10950-009-9176-9
   Web of Science ®Google Scholar
• Akkar, S., O. Kale, E. Yenier, and J. J. Bommer. 2011. “The High-Frequency Limit of Usable Response Spectral Ordinates from Filtered Analogue and Digital Strong-Motion Accelerograms.” Earthquake Engineering and Structural Dynamics 40 (12): 1387–1401. doi: 10.1002/eqe.1095
   Web of Science ®Google Scholar
• Alavi, A. H., and A. H. Gandomi. 2011. “Prediction of Principal Ground-Motion Parameters Using a Hybrid Method Coupling Artificial Neural Networks and Simulated Annealing.” Computers and Structures 89 (23–24): 2176–2194. doi: 10.1016/j.compstruc.2011.08.019
   Web of Science ®Google Scholar
• Alavi, A. H., A. H. Gandomi, M. Modaresnezhad, and M. Mousavi. 2011. “New Ground-Motion Prediction Equations Using Multi Expression Programing.” Journal of Earthquake Engineering 15 (4): 511–536. doi: 10.1080/13632469.2010.526752
   Web of Science ®Google Scholar
• Anderson, J. G., and Y. Lei. 1994. “Nonparametric Description of Peak Acceleration as a Function of Magnitude, Distance, and Site in Guerrero, Mexico.” Bulletin of the Seismological Society of America 84 (4): 1003–1017.
   Web of Science ®Google Scholar
• Aster, R. C., B. Borchers, and C. Thurber. 2012. Parameter Estimation and Inverse Problems. Burlington, MA: Academic Press.
   Google Scholar
• Boore, D. M. 1973. “Empirical and Theoretical Study of Near-Fault Wave Propagation.” In Proceedings of the 5th World Conference on Earthquake Engineering, Rome, Italy.
   Google Scholar
• Boore, D. M., and G. M. Atkinson. 2008. “Ground-Motion Prediction Equations for the Average Horizontal Component of PGA, PGV, and 5%-Damped PSA at Spectral Periods Between 0.01 s and 10.0 s.” Earthquake Spectra 24 (1): 99–138. doi: 10.1193/1.2830434
   Web of Science ®Google Scholar
• Cabalar, A. F., and A. Cevik. 2009. “Genetic Programming-Based Attenuation Relationship: An Application of Recent Earthquakes in Turkey.” Computers and Geosciences 35 (9): 1884–1896. doi: 10.1016/j.cageo.2008.10.015
   Web of Science ®Google Scholar
• Friedman, J. H. 1991. “Multivariate Adaptive Regression Splines.” The Annals of Statistics 19 (1): 1–141. doi: 10.1214/aos/1176347963
   Web of Science ®Google Scholar
• Gandomi, A. H., A. H. Alavi, M. Mousavi, and S. M. Tabatabaei. 2011. “A Hybrid Computational Approach to Derive New Ground-Motion Prediction Equations.” Engineering Applications of Artificial Intelligence 24 (4): 717–732. doi: 10.1016/j.engappai.2011.01.005
   Web of Science ®Google Scholar
• Gandomi, A. H., G. J. Yun, and A. H. Alavi. 2013. “An Evolutionary Approach for Modeling of Shear Strength of RC Deep Beams.” Materials and Structures 46 (12): 2109–2119. doi: 10.1617/s11527-013-0039-z.
   Web of Science ®Google Scholar
• Gulerce, Z., B. Kargıoğlu, and N. A. Abrahamson. Forthcoming. “Turkey-Adjusted NGA-W1 Horizontal Ground Motion Prediction Models.” Submitted to Earthquake Spectra.
   Google Scholar
• Gutenberg, B., and C. F. Richter. 1956. “Earthquake Magnitude, Intensity, Energy and Acceleration.” Bulletin of the Seismological Society of America 46 (2): 105–195.
   Google Scholar
• Myers, R. H., and D. C. Montgomery. 2002. Response Surface Methodology: Process and Product Optimization Using Designed Experiments. New York: Wiley.
   Google Scholar
• Nesterov, Y. E., and A. S. Nemirovski. 1994. Interior-Point Polynomial Algorithms in Convex Programming. Philadelphia, PA: Society for Industrial and Applied Mathematics.
   Google Scholar
• Neter, J., M. Kutner, W. Wasserman, and C. Nachtsheim. 1996. Applied Linear Statistical Models. Boston, MA: WCB/McGraw-Hill.
   Google Scholar
• Perus˘, I., and P. Fajfar. 2010. “Ground-Motion Prediction by a Non-Parametric Approach.” Earthquake Engineering and Structural Dynamics 39 (12): 1395–1416.
   Web of Science ®Google Scholar
• Power, M., B. Chiou, N. Abrahamson, Y. Bozorgnia, T. Shantz, and C. Roblee. 2008. “An Overview of the NGA Project.” Earthquake Spectra 24 (1): 3–21. doi: 10.1193/1.2894833
   Web of Science ®Google Scholar
• Spudich, P., W. B. Joyner, A. G. Lindh, D. M. Boore, B. M. Margaris, and J. B. Fletcher. 1999. “SEA99: A Revised Ground Motion Prediction Relation for Use in Extensional Tectonic Regimes.” Bulletin of the Seismological Society of America 89 (5): 1156–1170.
   Web of Science ®Google Scholar
• Tavakoli, B., and S. Pezeshk. 2007. “A New Approach to Estimate a Mixed Model-Based Ground Motion Prediction Equation.” Earthquake Spectra 23 (3): 665–684. doi: 10.1193/1.2755934
   Web of Science ®Google Scholar
• Tezcan, J., and Q. Cheng. 2012. “Support Vector Regression for Estimating Earthquake Response Spectra.” Bulletin of Earthquake Engineering 10 (4): 1205–1219. doi: 10.1007/s10518-012-9350-2
   Web of Science ®Google Scholar
• Trifunac, M. D. 1976. “Preliminary Analysis of the Peaks of Strong Earthquake Ground Motion—Dependence of Peaks on Earthquake Magnitude, Epicentral Distance, and Recording Site Conditions.” Bulletin of the Seismological Society of America 66 (1): 189–219.
   Web of Science ®Google Scholar
• Weber, G. W., İ. Batmaz, G. Köksal, P. Taylan, and F. Yerlikaya-Özkurt. 2012. “CMARS: A New Contribution to Nonparametric Regression with Multivariate Adaptive Regression Splines Supported by Continuous Optimization.” Inverse Problems in Science and Engineering 20 (3): 371–400. doi: 10.1080/17415977.2011.624770
   Web of Science ®Google Scholar
• Yerlikaya, F. 2008. “A New Contribution to Nonlinear Robust Regression and Classification with MARS and Its Application to Data Mining for Quality Control in Manufacturing.” MSc diss., Middle East Technical University, Turkey.
   Google Scholar
• Yerlikaya-Özkurt, F., İ. Batmaz, and G. W. Weber. Forthcoming. “A Review and New Contribution on Conic Multivariate Adaptive Regression Splines (CMARS): A Powerful Tool for Predictive Data Mining.” In Modeling, Optimization, Dynamics and Bioeconomy, Vol. of Springer Proceedings in Mathematics & Statistics, edited by D. Zilberman and A. Pinto.: Springer.
   Google Scholar