Peak ground acceleration prediction by fuzzy logic modeling for Iranian plateau

Abstract

In this study, fuzzy logic modeling is applied to a complex and nonlinear set of data to predict both horizontal and vertical peak ground accelerations in Iranian plateau. The data used for the model include an up-to-date seismic catalogue from earthquakes in Iran for prediction of both horizontal and vertical acceleration of a probable earthquake. Fuzzy logic toolbox on MATLAB program was used for modeling. Earthquake magnitude ranging from 4 to 7.4, source-to-site distance from 7 to 80 km and three different site conditions were considered: rock, stiff soil and soft soil. Results are compared with those from worldwide and regional attenuation relationships, which show the higher capability of the model in comparison with the other models. After training the model, testing of the fuzzy model with the remaining data set was performed to confirm the accuracy of the model. Changes in the peak ground accelerations in connection with changes in input parameters are studied which are in agreement with basic characteristics of earthquake input motions.

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References

  1. Abrahamson NA, Silva WJ (2008) Summary of the Abrahamson and Silva NGA ground-motion relations. Earthq Spectra 24:67–97. https://doi.org/10.1193/1.2924360

    Article  Google Scholar 

  2. Abrahamson NA, Silva WJ, Kamai R (2014) Summary of the ASK14 ground motion relation for active crustal regions. Earthq Spectra 30(3):1025–1055. https://doi.org/10.1193/070913EQS198M

    Article  Google Scholar 

  3. Ahumada A, Altunkaynak A, Ayoub A (2015) Fuzzy logic-based attenuation relationships of strong motion earthquake records. Expert Syst Appl 42(3):1287–1297. https://doi.org/10.1016/j.eswa.2014.09.035

    Article  Google Scholar 

  4. Alimoradi A, Pezeshk S, Naeim F, Frigui H (2005) Fuzzy pattern classification of strong ground motion records. J Earthq Eng 9(3):307–332. https://doi.org/10.1080/13632460509350544

    Article  Google Scholar 

  5. Ambraseys N, Douglas J (2000) Reappraisal of the effect of vertical ground motions on response. In: ESEE Report 00-4. Department of Civil and Environmental Engineering, Imperial College, London, http://www.esee.cv.ic.ac.uk/reports.htm

  6. Ambraseys NN, Simpson KA (1996) Prediction of vertical response spectra in Europe. Earthq Eng Struct Dyn 25(4):401–412. https://doi.org/10.1002/(SICI)1096-9845(199604)25:4%3c401:AID-EQE551%3e3.0.CO;2-B

    Article  Google Scholar 

  7. Ambraseys NN, Simpson KA, Bommer JJ (1996) Prediction of horizontal response spectra in Europe. Earthq Eng Struct Dyn 25(4):371–400. https://doi.org/10.1002/(SICI)1096-9845(199604)25:4%3c371:AID-EQE550%3e3.0.CO;2-A

    Article  Google Scholar 

  8. Ambraseys NN, Douglas J, Sarma SK, Smit PM (2005a) 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 3:1–53. https://doi.org/10.1007/s10518-005-0183-0

    Article  Google Scholar 

  9. Ambraseys NN, Douglas J, Sarma SK, Smit PM (2005b) Equations for the estimation of strong ground motions from shallow crustal earthquakes using data from europe and the middle east: vertical peak ground acceleration and spectral acceleration. Bull Earthq Eng 3:55–73. https://doi.org/10.1007/s10518-005-0186-x

    Article  Google Scholar 

  10. Amiri GG, Mahdavian A, Manouchehri-Dana F (2007) Attenuation relationships for Iran. J Earthq Eng 11(4):469–492. https://doi.org/10.1080/13632460601034049

    Article  Google Scholar 

  11. Anderson JG (1991) Strong motion seismology. Rev Geophys 29:700–720

    Article  Google Scholar 

  12. Atkinson GM, Boore DM (2003) Empirical ground-motion relations for subduction zone earthquakes and their application to Cascadia and other regions. Bull Seismol Soc Am 93(4):1703–1729. https://doi.org/10.1785/0120080108

    Article  Google Scholar 

  13. Bommer JJ, Elnashai AS, Chlimintzas GO, Lee D (1998) Review and development of response spectra for displacement based seismic design. In: ESEE Report 98-3. Department of Civil Engineering, Imperial College, London

  14. Boore DM (1983) Strong-motion seismology. Rev Geophys Space Phys 21(6):1308–1318

    Article  Google Scholar 

  15. Boore DM, Atkinson GM (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. Earthq Spectra 24:99–138. https://doi.org/10.1193/1.2830434

    Article  Google Scholar 

  16. Boore DM, Joyner WB, Fumal TE (1993) Estimation of response spectra and peak accelerations from western North American earthquakes: an interim report. In: Open-file report. US Geological Survey, pp 93–509

  17. Boore DM, Joyner WB, Fumal TE (1997) Equations for estimating horizontal response spectra and peak acceleration from western North American earthquakes: a summary of recent work. Seismol Res Lett 68:128–153

    Article  Google Scholar 

  18. Boore DM, Stewart JP, Seyhan E, Atkinson GM (2014) NGA-West2 equations for predicting PGA, PGV, and 5% damped PSA for shallow crustal earthquakes. Earthq Spectra 30:1057–1085. https://doi.org/10.1193/070113EQS184M

    Article  Google Scholar 

  19. Bozorgnia Y, Campbell KW (2004) The vertical-to-horizontal response spectral ratio and tentative procedures for developing simplified V/H and the vertical design spectra. J Earthq Eng 8(2):175–207. https://doi.org/10.1080/13632460409350486

    Article  Google Scholar 

  20. Bozorgnia Y, Campbell KW, Niazi M (2000) Observed spectral characteristics of vertical ground motion recorded during worldwide earthquakes from 1957 to 1995. In: Proceedings of twelfth world conference on earthquake engineering, paper no. 2671

  21. Campbell KW, Bozorgnia Y (2000) New empirical models for predicting near-source horizontal, vertical, and V/H response spectra: implications for design. In: Proceedings of the sixth international conference on seismic zonation

  22. Campbell KW, Bozorgnia Y (2003) Updated near-source ground-motion (attenuation) relations for the horizontal and vertical components of peak ground acceleration and acceleration response spectra. Bull Seismol Soc Am 93(1):314–331. https://doi.org/10.1785/0120020029

    Article  Google Scholar 

  23. Campbell KW, 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 0.01 to 10 s. Earthq Spectra 24:139–171. https://doi.org/10.1193/1.2857546

    Article  Google Scholar 

  24. Campbell KW, Bozorgnia Y (2014) NGA-West2 ground motion model for the average horizontal components of PGA, PGV, and 5% damped linear acceleration response spectra. Earthq Spectra 30:1087–1115. https://doi.org/10.1193/062913EQS175M

    Article  Google Scholar 

  25. Chiou BSJ, Youngs RR (2008) An NGA model for the average horizontal component of peak ground motion and response spectra. Earthq Spectra 24:173–215. https://doi.org/10.1193/1.2894832

    Article  Google Scholar 

  26. Chiou BSJ, Youngs RR (2014) Update of the Chiou and Youngs NGA model for the average horizontal component of peak ground motion and response spectra. Earthq Spectra 30:1117–1153. https://doi.org/10.1193/072813EQS219M

    Article  Google Scholar 

  27. Douglas J (2001) A critical reappraisal of some problems in engineering seismology. Ph.D. Thesis, University of London

  28. Douglas J (2002) Earthquake ground motion estimation using strong-motion records: a review of equation for the estimation of peak ground acceleration and response spectral ordinate. Earth Sci Rev 61:43–104. https://doi.org/10.1016/S0012-8252(02)00112-5

    Article  Google Scholar 

  29. Douglas J (2004) Ground motion estimation equations 1964–2003: reissue of ESEE report 01-1: ‘A comprehensive worldwide summary of strong-motion attenuation relationships for peak ground acceleration and spectral ordinates (1969 to 2000)’ with corrections and additions. In: Technical report 04-001-SM. Department of Civil and Environmental Engineering; Imperial College of Science. Technology, and Medicine; London

  30. Idriss IM (1990) Response of soft soil sites during earthquakes. In: Duncan JM (ed) Proceedings, H. Bolton seed memorial symposium, vol 2. BiTech Published, Vancouver, pp 273–289

    Google Scholar 

  31. Idriss IM (2008) An NGA empirical model for estimating the horizontal spectral values generated by shallow crustal earthquakes. Earthq Spectra 24:217–242. https://doi.org/10.1193/1.2924362

    Article  Google Scholar 

  32. Idriss IM (2014) An NGA-West2 empirical model for estimating the horizontal spectral values generated by shallow crustal earthquakes. Earthq Spectra 30:1155–1177. https://doi.org/10.1193/070613EQS195M

    Article  Google Scholar 

  33. Jorjiashvili N, Yokoi T, Javakhishvili Z (2012) Assessment of uncertainties related to seismic hazard using fuzzy analysis. Nat Hazards 60(2):501–515. https://doi.org/10.1007/s11069-011-0026-z

    Article  Google Scholar 

  34. Joyner WB (1987) Strong-motion seismology. Rev Geophys 25(6):1149–1160. https://doi.org/10.1029/RG025i006p01149

    Article  Google Scholar 

  35. Joyner WB, Boore DM (1981) Peak horizontal acceleration and velocity from strong-motion records including records from the 1979 Imperial Valley, California, earthquake. Bull Seismol Soc Am 71(6):2011–2038

    Google Scholar 

  36. Joyner WB, Boore DM (1988) Measurement, characterization, and prediction of strong ground motion. In: Proceedings of earthquake engineering and soil dynamics II, geotechnical division ASCE, 43–102

  37. Khademi MH (2002) Attenuation of peak and spectral accelerations in the Persian plateau. In: Proceedings of twelfth European conference on earthquake engineering. Paper reference 330

  38. Kobayashi S, Takahashi T, Matsuzaki S, Mori M, Fukushima Y, Zhao JX, Somerville PG (2000) A spectral attenuation model for Japan using digital strong motion records of JMA87 type. In: Proceedings of twelfth world conference on earthquake engineering, paper no. 2786

  39. Kramer SL (1996) Geotechnical earthquake engineering. Prentice-Hall, Inc, Upper Saddle River

    Google Scholar 

  40. Laurie G, Baise, Eric M (2011) Thompson, incorporating site effects in ground motion prediction equations. In: Final technical report. USGS Award Number G11AP20033

  41. Lawson RS, Krawinkler H (1994) Cumulative damage potential of seismic ground motion. In: Proceedings of tenth European conference on earthquake engineering, vol 2. pp: 1079–1086

  42. Mamdani EH, Assilian S (1975) An experiment in linguistic synthesis with a fuzzy logic controller. Int J Man-Mach Stud 7(1):1–13

    Article  Google Scholar 

  43. MATLAB (2000) Fuzzy logic toolbox for use with MATLAB: user’s guide. In: Fourth printing, revised for MATLAB 6.0. The Math Works Inc

  44. Mierlus-Mazilu I, Majercsik L (2010) Efficient methods for the classification of seismic damage potential of ground motions. Sci J Ser Math Modell Civ Eng 1:51–60

    Google Scholar 

  45. Ozmen B, Babsbug Erkan BB (2014) Probabilistic earthquake hazard assessment for Ankara and its environs. Turk J Earth Sci 23:462–474. https://doi.org/10.3906/yer-1302-6

    Article  Google Scholar 

  46. Road, Housing and Urban Development Research Center (2012) Iran strong motion network. http://www.bhrc.ac.ir/

  47. Sadigh K, Chang CY, Egan JA, Makdisi F, Youngs RR (1997) Attenuation relationships for shallow crustal earthquakes based on California strong motion data. Seismol Res Lett 68(1):180–189

    Article  Google Scholar 

  48. Shoushtari AV, Adnan AB, Zare M (2016) On the selection of ground–motion attenuation relations for seismic hazard assessment of the Peninsular Malaysia region due to distant Sumatran subduction intraslab earthquakes. Soil Dyn Earthq Eng 82:123–137. https://doi.org/10.1016/j.soildyn.2015.11.012

    Article  Google Scholar 

  49. Sugeno M (1985) Industrial applications of fuzzy control. Elsevier Science Pub. Co, New York

    Google Scholar 

  50. Sun SS, Sung DC, Yong RK (2002) Empirical evaluation of a fuzzy logic-based software quality prediction model. http://dl.acm.org/citation.cfm?id=765833. Retrieved on 15/05/2016

  51. Thomas S, Pillai GN, Pal K, Jagtap P (2016) Prediction of ground motion parameters using randomized ANFIS (RANFIS). Appl Soft Comput 40:624–634. https://doi.org/10.1016/j.asoc.2015.12.013

    Article  Google Scholar 

  52. Tsiftzis I, Andreadis I, Elenas A (2006) Fuzzy system for seismic signal classification. IEE Proc Vis Image Signal Process 153(2):109–114. https://doi.org/10.1049/ip-vis:20050068

    Article  Google Scholar 

  53. Wadia-fascetti S, Gunes B (2000) Earthquake response spectra models incorporating fuzzy logic with statistics. Comput Aided Civ Infrastruct Eng 15(2):134–146. https://doi.org/10.1111/0885-9507.00178

    Article  Google Scholar 

  54. Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353

    Article  Google Scholar 

  55. Zare M, Sabzali S (2006) Spectral attenuation of strong motions in Iran. In: Third international symposium on the effects of surface geology on seismic motion grenoble, France

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Acknowledgements

We thank the Road, Housing and Urban Development Research Centre, Tehran, Iran, for providing us with the strong-motion database. The authors also gratefully acknowledge the support from Ali Beitollahi, Head of Engineering Seismology Department at this research center, and Mehdi Zare from International Institute of Earthquake Engineering and Seismology (IIEES) for their critical and helpful comments, which have led to significant improvement of the article. The authors also thank Ataturk University for using MATLAB at its computer laboratory.

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Correspondence to Babak Karimi Ghalehjough.

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Karimi Ghalehjough, B., Mahinroosta, R. Peak ground acceleration prediction by fuzzy logic modeling for Iranian plateau. Acta Geophys. 68, 75–89 (2020). https://doi.org/10.1007/s11600-019-00394-z

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Keywords

  • Attenuation relationships
  • Fuzzy logic modeling
  • Earthquake input motion
  • Peak ground acceleration