Liquefaction prediction using rough set theory

Document Type : Research Note

Authors

1 Department of Civil Engineering, University of Guilan, Rasht, P.O. Box 3756, I.R. Iran

2 Department of Civil Engineering, University of Guilan, Rasht, I.R. Iran

Abstract

Evaluation of liquefaction is one of the most important issues in geotechnical engineering. Liquefaction prediction depends on many factors and the relationship between these factors is non-linear and complex. Different methods have been proposed by different authors for liquefaction prediction. These methods are mostly based on statistical approaches and neural network.
In this paper a new approach based on Rough Set data mining procedure is presented for liquefaction prediction. The Rough set theory is a mathematical approach for analysis of imperfect knowledge or unclear description of objects. In this approach the decision rules are derived from conditional attributes in Rough Set analysis and the results are compared with actual field observations. The results of this study indicate that using this method can be helpful for liquefaction prediction and can reduce unnecessary costs in site investigation process.

Keywords

Main Subjects


References:
1. Madabhushi, G., Knappett, J., and Haigh, S., Design of Pile Foundation in Liquefiable Soils, published by imperial collage press London WC2H 9HE (2010).
2. Seed, H.B. and Idriss, I.M. "Simplified procedure for evaluating soil liquefaction potential", Journal of the Soil Mechanics and Foundations Division, ASCE, 97, pp. 1249-1273 (1971).
3. Seed, H.B., Idriss, I.M., Makdisi, F., and Banerjee, N. "Representation of irregular stress time histories by equivalent uniform stress series in liquefaction analyses", Report No. UCB/EERC-75/29, Earthquake Engineering Research Centre, U.C. Berkeley (1975).
4. Ishihara, K., and Yasuda, S. "Sand liquefaction in hollow cylinder torsion under irregular excitation", Soils and Found, 15(1), pp. 45-59 (1975).
5. Seed, H.B. "Soil liquefaction and cyclic mobility evaluation for level ground during Earthquakes", Journal of Geotechnical Engineering, ASCE, 105, pp. 201-255 (1979).
6. Seed, H.B., and Idriss, I.M., Ground Motions and Soil Liquefaction During Earthquakes, Earthquake Engineering Research, Institute Monograph (1982).
7. Seed, H.B., Tokimatsu, K., Harder, L.F., and Chung, R.M. "The influence of SPT procedures in soil liquefaction resistance evaluations", Journal of Geotechnical Engineering, ASCE, 111(12), pp. 1425-1445 (1985).
8. Youd, T.L., Idriss, I.M. Andrus, R.D. Arango, I., Castro, G., Christian, J.T., Dobry, R., Liam Finn, W.D.L., Harder, L.F. Jr., Hynes, M.E., Ishihara, K., Koester, J.P., Liao, S.S.C., Marcuson, W.F., III, Martin, G.R., Mitchell, J.K., Moriwaki, Y., Power, M.S., Robertson, P.K., Seed, R.B., Stokoe, K.H., II, "Liquefaction resistance of soils: Summary report from the 1996 NCEER and 1998 NCEER/NSF workshops on evaluation of liquefaction resistance of soils", J. of Geotech. Geoenviron. Eng., 127(10), pp. 817-833 (republication 137 with correct authors) (2001).
9. Dobry, R., Ladd, R.S., Yokel, F.Y., Chung, R.M., and Powell, D. "Prediction of pore water pressure buildup and liquefaction of sands during earthquakes by the cyclic strain method", Building Science Series, National Bureau of Standards, US Department of Commerce, US Governmental Printing Office, 138, Washington, DC (1982).
10. Okada, N., and Nemat-Nasser, S. "Energy dissipation in inelastic  flow of saturated cohesionless granular media", Geotechnique, 44(1), pp. 1-19 (1994).
11. Trifunac, M. "Empirical criteria for liquefaction in sands via standard penetration tests and seismic wave energy", Soil Dynamics and Earthquake Engineering, 14, pp. 419-426 (1995).
12. Kayen, R.E., and Mitchell, J.K. "Assessment of liquefaction potential during earthquakes by arias intensity", ASCE, Journal of Geotechnical and Geoenvironmental Engineering, 123(12), pp. 1162-1174 (1997).
13. Green, R. "Energy based evaluation and remediation of liquefiable soils", PhD Dissertation, Virginia Polytechnic Institute and State University (2001).
14. Rahman, M.S., and Wang, J. "Fuzzy neural network models for liquefaction prediction", Soil Dynamics and Earthquake Engineering, 22(8), pp. 685-694 (2002).
15. Chen, Y.R., Hsieh, S.C., Chen, J.W., and Shih, C.C. "Energy-based probabilistic evaluation of soil liquefaction", Soil Dynamics and Earthquake Engineering, 25(1), pp. 55-68 (2005).
16. Baziar, M.H., and Jafarian, Y. "Assessment of liquefaction triggering using strain energy concept and ANN model: Capacity energy", Soil Dynamics and Earthquake Engineering, 27, pp. 1056-1072 (2007).
17. Hanna, A.M., Ural, D., and Saygili, G. "Neural network model for liquefaction potential in soil deposits using Turkey and Taiwan earthquake data", Soil Dynamics and Earthquake Engineering, 27(6), pp. 521-540 (2007).
18. Khozaghi, S.S.H., and Choobbasti, A.J.A. "Predicting of liquefaction potential in soils using artificial neural networks", Electronic Journal of Geotechnical Engineering, 12, Bundle C (2007).
19. Baykasoglu, A., Cevik, A., Ozbakir, L., and Kulluk, S. "Generating prediction rules for liquefaction through data mining", Expert Systems with Applications, 36, pp. 12491-12499 (2009).
20. Abbaszadeh Shahri, A. "Assessment and prediction of liquefaction potential using different artificial neural network models: A case study", Geotechnical and Geological Engineering, 34(3) p. 807 (2016).
21. Pawlak, Z., Rough Sets: Theoretical Aspects of Reasoning about Data, Kluwer Academic Publishers, Dordrecht, Boston (1991).
22. Hung, C.T., Chang, J.R., Lin, J.D., and Tzeng, G.H., Rough Set Theory in Pavement Maintenance Decision, Springer-Verlag Berlin Heidelberg (2009).
23. Lee, C.S. "A framework of adaptive T-S type roughfuzzy inference systems (ARFIS)", PhD Thesis, The University of Western Australia (2009).
24. Stark, T.D., and Olson, S.M. "Liquefaction resistance using CPT and field case histories", J. Geotech. Eng. Div, ASCE, 121(12) pp. 856-869 (1995).
25. Arabani, M. and Lashteh Neshaei, M.A. "Application of rough set theory as a new approach to simplify dams location", Scientia Iranica, 13(2), pp. 152-158 (2006).
26. Lashteh Neshaei, M.A., and Pirouz, M. "Rough Sets theory in site selection decision making for water reservoirs", Computational Methods in Civil Engineering, 1(1) pp. 85-94 (2010).
27. Arabani, M., and Pirouz, M. "Water treatment plant site location using rough set theory", Environmental Monitoring and Assessment, 188(10) p. 552 (2016).
28. Arabani, M., Haghi, A.K., and Amani, B. "Making a decision between the rehabilitation and reconstruction of asphalt pavements using the rough-set theory", Scientia Iranica, Transaction A: Civil Engineering, 16,(2) pp. 116-125 (2009).
29. Arabani, M., and Amani, B. "Evaluating the parameters affecting urban trip-generation", Iranian Journal of Science & Technology, Transaction B, Engineering, 31(B5), pp. 547-560 (2009).
30. Chattefuee S., and Hadi A.S., Regression Analysis by Example, 4th edition, John Wiley & Sons (2006).