Adaptive Fuzzy C-Mean Clustering of Ground Motion Prediction Equations

Document Type : Seismology and Engineering Seismology

Authors

Arak University

Abstract

Selection of Ground Motion Prediction Equations (GMPEs) within the Seismic Hazard Analysis (SHA) is an important and timely research line of inquiry. A set of 22 regional and worldwide GMPEs have been selected in this research for the purpose of classification. They are classified into clusters in which each cluster is defined to have the most dissimilarity with the other clusters as well as having the most similarity within the cluster. The C-mean clustering algorithm is modified and adapted in order to be applicable in the current study. In addition, six groups are defined for different focal mechanisms and soil types. Then, the GMPE clustering is performed for each group and the obtained clusters are proposed and discussed. The results confirm that the obtained spectral ordinated from GMPEs of different clusters can meaningfully differed from each other.

Keywords


  1. Elnashai, A.S. and Di Sarno, L. (2008) Fundamentals of Earthquake Engineering. John Wiley and Sons, Ltd, New York.
  2. Douglas, J. (2011) Ground-Motion Prediction Equations 1964–2010. Pacific Earthquake Engineering Research Center, College of Engineering, University of California, Berkeley.
  3. Mousavi, M., Ansari, A., Zafarani, H., and Azarbakht, A. (2012) Selection of ground motion prediction models for seismic hazard.
  4. Hoeppner, F., Klawonn, F., Kruse, R., and Runkler, T. (1999) Fuzzy Cluster Analysis: Methods for Classification, Data Analysis and Image Recognition. John Willey and Sons, Ltd, New York.
  5. Gan, G., Ma, C., and Wu, J. (2007) Data Clustering: Theory, Algorithms, and Applications. Society for Industrial and Applied Mathematics, American Statistical Association, Philadelphia.
  6. Jain, A. K. and Dubes, R.C. (1988) Algorithms for Clustering Data. Prentice Hall, Inc., New Jersey.
  7. Zadeh, L.A. (1965) Fuzzy sets. Inf. Control., 8(3), 338-353.
  8. Bezdek, J.C. (1981) Pattern Recognition with Fuzzy Objective Function Algorithms. Springer Science and Business Media, Plenum Press, New York.
  9. Kaklamanos, J., Baise, L.G. and Boore, D.M. (2011) Estimating unknown input parameters when implementing the NGA ground-motion prediction equations in engineering practice. Earthquake Spectra. 27(4), 1219–1235.
  10. Beyer, K. and Bommer, J.J. (2006) Relationships between median values and between aleatory variabilities for different definitions of the horizontal component of motion. Bull. Seismol. Soc. Am. 96(4A), 1512-1522.
  11. Ghodrati Amiri, G., Khorasani, M., Mirza Hessabi, R., and Razavian Amiri, S.A. (2009) Ground-motion prediction equations of spectral ordinates and arias intensity for Iran. J. Earthq. Eng., 14(1), 1-29.
  12. Boore, D.M. and Atkinson, G.M. (2008) Ground-motion prediction equations for the average horizontal component of PGA, PGV, and 5%-damped PSA at spectral periods between 0.01 sec and 10.0 sec. Earthquake Spectra, 24(1), 99-138.
  13. Campbell, K.W. and Bozorgnia, Y. (2008) NGA ground motion model for the geometric mean horizontal component of PGA, PGV, PGD and 5% damped linear elastic response spectra for periods ranging from 0.01sec to 10 sec. Earthquake Spectra, 24(1), 139-171.
  14. Abrahamson, N. and Silva, W. (2008) Summary of the Abrahamson and Silva NGA ground-motion relations. Earthquake Spectra, 24(1), 67-97.
  15. Chiou, B.S.J. and Youngs, R.R. (2008) An NGA model for the average horizontal component of peak ground motion and response spectra. Earthquake Spectra, 24(1), 173-215.
  16. Idriss, I.M. (2008) An NGA empirical model for estimating the horizontal spectral values generated by shallow crustal earthquakes. Earthquake Spectra, 24(1), 217-242.
  17. Kuehn, N.M., Scherbaum, F., and Riggelsen, C. (2009) Deriving empirical ground-motion models: balancing data constraints and physical assumptions to optimize prediction capability. Bull. Seismol. Soc. Am., 99(4), 2335–2347.
  18. Ambraseys, N.N., Douglas, J., Sarma, S.K. and Smit, P.M. (2005) Equations for the estimation of strong ground motions from shallow crustal earthquakes using data from Europe and the Middle East: horizontal peak ground acceleration and spectral acceleration. Bull. Earthq. Eng., 3(1), 1–53.
  19. Akkar, S. and Bommer, J.J. (2010) Empirical equations for the prediction of PGA, PGV and spectral accelerations in Europe, the Mediterranean region and the Middle East. Seismol. Res. Lett., 81(2), 195-206.
  20. Bindi, D., Luzi, L., Massa, M. and Pacor, F. (2010) Horizontal and vertical ground motion prediction equations derived from the Italian Accelerometric Archive (ITACA). Bull. Earthq. Eng., 8(5), 1209-1230.
  21. Zhao, J.X., Zhang, J., Asano, A., Ohno, Y., Oouch, T., Takahashi, T., Ogawa, H., Irikura, K., Thio, H.K., Somerville, P.G., Fukushima, Y., and Fukushima, Y. (2006) Attenuation relations of strong ground motion in Japan using site classification based on predominant period. Bull. Seismol. Soc. Am., 96(3), 898-913.
  22. Kalkan, E. and Gulkan, P. (2004) Site-dependent spectra derived from ground motion records in Turkey. Earthquake Spectra, 20(4), 1111-1138.
  23. Ozbey, C., Sari, A., Manuel, L., Erdik, M., and Fahjan, Y. (2004) An empirical attenuation relationship for Northwestern Turkey ground motion using a random effects approach. Soil Dynam. Earthquake Eng. 24(2), 115-125.
  24. Akkar, S. and Cagnan, Z. (2010) A local ground-motion predictive model for Turkey, and its comparison with other regional and global ground-motion models. Bull. Seismol. Soc. Am., 100(6), 2978–2995.
  25. Ghasemi, H., Zare, M., Fukushima, Y., and Koketsu, K. (2009) An empirical spectral ground-motion model for Iran. J. Seismol., 13(4), 499-515.
  26. Saffari, H., Kuwata, Y., Takada, S., and Mahdavian, A. (2012) Updated PGA, PGV, and spectral acceleration attenuation relations for Iran. Earthq. Spectra, 28(1), 257-276.
  27. Zafarani, H. and Soghrat, M. (2012) Simulation of ground motion in the Zagros region, Iran using the specific barrier model and stochastic method. Bull. Seismol. Soc. Am., 102(5), 2031-2045.
  28. Sharma, M.L., Douglas, J., Bungam, H., and Kotadia, J. (2009) Ground-motion prediction equations based on data from the Himalayan and Zagros regions. J. Earthq. Eng., 13(8), 1191-1210.
  29. Fukushima, Y., Berge-Thierry, C., Volant, P., Griot-Pommera, D.A., and Cotton, F. (2003) Attenuation relation for West Eurasia determined with recent near fault records from California, Japan and Turkey. J. Earthq. Eng., 7(4), 573-598.
  30. Xie, X.L. and Beni, G. (1991) A validity measure for fuzzy clustering. IEEE Trans. Pattern Anal. Machine Intell., 13(8), 841-847.