The soil liquefaction assessments that are widely used in recent practices demand a soil parameters obtained from Standard Penetration Test (SPT), or Cone Penetration Test (CPT). This research suggests a new approach to do soil liquefaction assessment with the microtremor data which is easier and more economic. The analysis presented in this research consists of 93 spots within the southern part of Tainan City, Taiwan, where borehole data has been obtained and microtremor data is recorded. The final model obtained from Artificial Neural Network (ANN) will explain the relationship between microtremor parameters as the input and liquefaction potential as the output. Input parameters of microtremor data consists of (1) amount of high peak occurrence, (2) amount of low peak occurrence, (3-7) frequencies of each peak, (8) amount of valley occurrence, (9-11) frequencies of each valley, with the total of 11 input parameters. The output target is derived from SPT data to calculate soil liquefaction Potential Index (LPI) that can be categorized into (1) Non-liquefiable (LPI<5) and (2) Liquefiable (LPI>5). Variation in ANN training covers different amounts of input parameters, ranging from 3 to 11 parameters. The best performance is shown in 10 input parameters (except input 8) with the success rate of 85.2%. The result shows that microtremor observation with the help of ANN can predict liquefaction potential.

Almendros, J., F. Luzon, and A. Posadas, 2004, Microtremor Analyses at Teide Volcano (Canary Islands, Spain): Assessment of Natural Frequencies of Vibration Using Time-dependent Horizontal-to-vertical Spectral Ratios, Pure and Applied Geophysics 161, page 1579 – 1596
Artusi, R., P. Verderio, and E. Marubini, 2002, Bravais-Pearson and Spearman correlation coefficients: meaning, test of hypothesis and confidence interval, The International Journal of Biological Markers, Vol. 17 no. 2, page 148 - 151
Boulanger, R.W., and I.M. Idriss, 2006, Liquefaction Susceptibility Criteria for Silts and Clays, ASCE Journal of Geotechnical and Geoenvironmental Engineering, 133(6), page 641-652
Central Geological Survey, 2005, Underground geological and engineering environmental investigations at Hsinchu, Miaoli, and Tainan metropolitans, Report No. 92 – 94, Taipei, Taiwan
Chang, S-K., Lee, D-H., Wu, J-H., Juang, C.H., 2011, Rainfall-based criteria for assessing slump rate of mountainous highway slopes: A case study of slopes along Highway 18 in Alishan, Taiwan, Engineering Geology 118, page 63 - 74
Choobbasti, A.J., M. Naghizadehronki, S. Rezaei, 2015, Liquefaction assessment by microtremor measurements in Babol city, 5th International Conference on Geotechnique, Construction Materials and Environment, Osaka, Japan
Dongare, A.D., R.R. Kharde, A.D. Kachare, 2012, Introduction to Artificial Neural Network, International Journal of Engineering and Innovative Technology (IJEIT) Vol.2, Issue 1, July 2012, page 189 – 194
Fawcett, T., 2006, An introduction to ROC analysis, Pattern Recognition Letters 27, page 861 - 874
Ghaboussi, Jamshid, and Wilson, E.L., 1973, Liquefaction and Analysis of Saturated Granular Soils, World Conference on Earthquake Engineering, 5th, Chile 1969, Proceeding Vol.3, page 74 - 87
Goh, A. T. C., 1994, Seismic liquefaction potential assessed by neural network, Journal of Geotechnical & Geoenvironmental Engineering, ASCE, 120(9), page 1467-1480.
Hardesty, K., W.W. Lorraine, and P. Bodin, 2010, Noise to signal: A microtremor study at liquefaction sites in the New Madrid Seismic Zone, Geophysics Vol.75, No.3 (May – June 2010), page B83 – B90
Huang, H-C., and Tseng, Y-S., 2002, Characteristics of Soil Liquefaction using H/V of Microtremors in Yuan-Lin area, Taiwan, Terrestrial, Atmospheric and Oceanic (TAO), Vol. 13, No.3, September 2002, page 325 - 338
Huang, S-T., Yang, K-M., Hung, J-H., Wu, J-C., Ting, H-H., Mei, W-W., Hsu, S-H., and M. Lee, 2004, Deformation front development at the northeast margin of the Tainan basin, Tainan-Kaohsiung area, Taiwan, Marine Geophysical Researches (2004) 25, page 139 - 156
Idriss, I.M., and R.W. Boulanger, 2008, Soil Liquefaction during Earthquakes, Earthquake Engineering Research Institute MNO-12, Oakland, California
Idriss, I.M., and R.W. Boulanger, 2010, CPT and SPT Based Liquefaction Triggering Procedures, Report No. UCD/CGM-14/01, Center for Geotechnical Modeling, Department of Civil & Environmental Engineering, College of Engineering, University of California at Davis
Idriss, I.M., and R.W. Boulanger, 2014, SPT-Based Liquefaction Triggering Procedures, Report No. UCD/CGM-10/02, Center for Geotechnical Modeling, Department of Civil & Environmental Engineering, College of Engineering, University of California at Davis
Iwasaki, T., Arakawa, T., Tokida, K., 1982, Simplified Procedures for Assessing Soil Liquefaction During Earthquakes, Proceedings of the Conference on Soil Dynamics and Earthquake Engineering, Southampton, UK, page 925– 939
Jefferies, M. and Been, K., 2006, Soil Liquefaction: A Critical State Approach, New York: CRC Press, 512 p.
Juang, C. H., and Chen, C. J., 1999, CPT-based liquefaction evaluation using artificial neural networks, Computer-Aided Civil and Infrastructure Engineering, 14(3), page 221-229.
Khaze, S.R., M. Masdari, and S. Hojjatkhah, 2013, Application of Artificial Neural Network in Estimating Participation in Elections, International Journal of Information Technology, Modeling and Computing (IJITMC) Vol.1, No.3,August 2013, page 23 - 31
Kiyono, J., Ono, Y., Sato, A., Noguchi, T., Rusnardi, R., 2011, Estimation of Subsurface Structure Based on Microtremor Observations at Padang, Indonesia. Division III, Civil Engineering, Environmental Engineering and Geological Engineering. ASEAN Eng J 1(3), page 69–84
Kiyono, J., 2016, Personal Discussion, unpublished
Kyaw, Z.L., S. Pramumijoyo, S. Husein, T.F. Fathani, and J. Kiyono, 2014, Investigation to the Local Site Effects During Earthquake Induced Ground Deformation Using Microtremor Observation in Yogyakarta, Central Java-Indonesia, Landslide Science for a Safer Geoenvironment, Vol. 3, page 241 - 249
Lange, N.A. and Forker, G.M., 1961, Handbook of Chemistry (10th Edition), New York: McGraw-Hill, 1969 p.
Lee, D-H., C-S. Ku, H. Yuan, 2004, A Study of the Liquefaction Risk Potential at Yuanlin, Taiwan, Engineering Geology 71, page 97 – 117
Lee, K.L. and Seed, H.B., 1967, Cyclic Stress Conditions causing Liquefaction of Sand: Am. Soc. Civil Engineers Proc. Jour. Soil Mechanics and Found. Div. Vol.93, no SM1, page 47 – 70
Liao, J., J. Meneses, E. Ortakci, Z. Zafir, 2010, Comparison of Three Procedures for Evaluating Earthquake-Induced Soil Liquefaction, Fifth International Conference on Recent Advances in Geotechnical Earthquake Engineering and Soil Dynamics, Paper No. 4.48a
Lin, C.C., 1963, Geology and Ecology of Taiwan Prehistory, Asian Perspectives 7 Special Taiwan Section, page 203 - 213
Lu, C-W., Chen, J-W., Min Chao, and Jeng, C-H., 2017, DKSField investigation of liquefaction-induced damage due to the 2016 Meinong earthquake in the Shi-Din area of Taiwan, Proceedings of the 19th International Conference on Soil Mechanics and Geotechnical Engineering, Seoul 2017, page 1549 – 1552
Maurer, B.W., R.A. Green, M. Cubrinovski, and B.A. Bradley, 2015(a), Assessment of CPT-based methods for liquefaction evaluation in a liquefaction potential index framework, Geotechnique 65, No.5, page 328 – 336
Maurer, B.W., R.A. Green, M. Cubrinovski, and B.A. Bradley, 2015(b), Fines-content effects on liquefaction hazard evaluation for infrastructure in Christchurch, New Zealand, Soil Dynamics and Earthquake Engineering 76, page 58 - 68
Ministry of Interior, 2011, Seismic Design Specifications and Commentary of Buildings of Taiwan, Taipei, Taiwan
Moustra, M., M. Avraamides, C. Christodoulou, 2011, Artificial Neural Network for Earthquake Prediction using Time Series Magnitude Data or Seismic Electric Signals, Expert Systems with Applications 38, page 15032 – 15039
Nakamura,Y., 1989, A Method for Dynamic Characteristics Estimation of Surface Layers using Microtremor on the Surface, Quarterly Report of RTRI Vol. 30 No.1, page 18–27
Nakamura, Y., 1996, Real Time Information Systems for Seismic Hazards Mitigation UrEDAS, HERAS and PIC, Quarterly Report of RTRI, Vol. 37, No. 3, page 112-127
Nakamura, Y., 2000, Clear Identification of Fundamental Idea of Nakamura's Technique and Its Applications, 12th World Conference on Earthquake Engineering, Auckland, New Zealand, 30 January – 4 February 2000
National Center for Research on Earthquake Engineering (NCREE), 2016, NCREE Report: The February 6, 2016 ML-6.6 Meinong, Taiwan Earthquake and Lessons Learned, March 31, 2016, 37 p.
Niksarlioglu, S., and F. Kulahci, 2013, An Artificial Neural Network Model for Earthquake Prediction and Relations between Environmental Parameters and Earthquakes, International Journal of Environmental, Chemical, Ecological, Geological and Geophysical Engineering Vol:7, No:2, page 87 – 90
Oommen, T., L.G. Baise, and R. Vogel, 2010, Validation and Application of Empirical Liquefaction Models, Journal of Geotechnical and Geoenvironmental Engineering, ASCE, December 2010, page 1618 - 1633
Rezaei, S., and A.J. Choobbasti, 2014, Liquefaction assessment using microtremor measurement, conventional method and artificial neural network (Case study: Babol, Iran), Front. Struct. Civ. Eng. 2014, 8(3), page 292 - 307
Rumelhart, D.R., G.E. Hinton, R.S. Williams, 1986, Learning Representations by Back-propagating Errors, Nature, 323, page 533 – 536
Sarah, D. and Soebowo, E., 2013, Liquefaction Due to the 2006 Yogyakarta Earthquake: Field Occurrence and Geotechnical Analysis, International Symposium on Earth Science and Technology, CINEST 2012, Procedia Earth and Planetary Science 6 ( 2013 ), page 383 – 389
Seed, H.B. and Idriss I.M., 1971, Simplified Procedure for Evaluating Soil Liquefaction Potential, Am. Soc. Civil Engineers Proc. Jour. Soil Mechanics and Found. Div. Vol. 92, No. SM6, page 105 - 134
Seed, R. B., K.O. Cetin, R. E. S. Moss, A.M. Kammerer, J. Wu, J.M. Pestana, M.F. Riemer, R.B. Sancio, J.D. Bray, R.E. Kayen, and A, Faris, 2003, Recent Advances in Soil Liquefaction Engineering: a Unified and Consistent Framework, Keynote presentation, 26th Annual ASCE Los Angeles Geotechnical Spring Seminar, Long Beach, CA.
Shahin, M.A., M.B. Jaksa, H.R. Maier, 2001, Artificial Neural Network Applications in Geotechnical Engineering, Australian Geomechanics, March 2001, page 49 - 62
Sharma, V., S. Rai, A. Dev, 2012, A comprehensive Study of Artificial Neural Networks, International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE) Vol. 2, Issue 10, October 2012, page 278 – 284
Singh, A.P., A. Shukla, M.R. Kumar, and M.G. Thakkar, 2017, Characterizing Surface Geology, Liquefaction Potential, and Maximum Intensity in the Kachchh Seismic Zone, Western India, through Microtremor Analysis, Bulletin of the Seismological Society of America, Vol. 107, No.3
Tada, T., I. Cho, and Y. Shinozaki, 2010, Analysis of Love-wave components in microtremors, Joint Conference Proceedings, 7th International Conference on Urban Earthquake Engineering (7CUEE) & 5th International Conference on Earthquake Engineering (5ICEE), Center for Urban Earthquake Engineering, Tokyo Institute of Technology, page 115-124 (http://www.cuee.titech.ac.jp/Japanese/Publications/Doc/conference_7th.pdf)
Tague, N.R., 2004, The Quality Toolbox 2nd Edition, ASQ Quality Press, pages 292 - 299
Terzaghi, Karl, and Peck, R.B., 1948, Soil Mechanics in Engineering Practice, New York: John Wiley and Sons, 566 p.
Tokeshi, J.K., Y. Sugimura, and T. Sasaki, 1996, Assessment of Natural Frequency from Microtremor Measurement using Phase Spectrum, 11th World Conference on Earthquake Engineering, paper no.309
Wang, M-H., M-H. Chen, and C-H. Loh, 2000, Liquefaction Potential Study of Taiwan, 12th World Conference on Earthquake Engineering, Auckland, New Zealand, 30 January – 4 February 2000
Wang, W., 1979, Some Findings in Soil Liquefaction, Research Report, Water Conservancy and Hydroelectric Power Scientific Research Institute, Beijing, August
Youd, T. L., I.M. Idriss, R.D. Andrus, I. Arango, G. Castro, J.T. Christian, R. Dobry, W.D. Liam Finn, L.F. Jr. Harder, M.E. Hynes, K. Ishihara, J.P. Koester, S.S.C. Laio, W.F. Marcuson III, G.R. Martin, J.K. Mitchell, Y. Moriwaki, M.S. Power, P.K. Robertson, R.B. Seed, K.H. Stokoe II, 2001, Liquefaction Resistance of Soils: Summary report from the 1996 NCEER and 1998 NCEER/NSF workshops on evaluation of liquefaction resistance of soils, ASCE Journal of Geotechnical and Geoenvironmental Engineering, 127(10), page 817–833
Zhang, H., Jeng, D-S., Cha, D. and Blumenstein, M., 2007, Parametric study on the Prediction of Wave-induced Liquefaction using an Artificial Neural Network Model, Journal of Coastal Research, SI 50 (Proceedings of the 9th International Coastal Symposium), page 374 – 378