Seismic liquefaction potential assessed by fuzzy comprehensive evaluation method

Liquefaction of loose, saturated granular soils during earthquakes poses a major hazard in many regions of the world. The determination of liquefaction potential of soils induced by earthquake is a major concern and an essential criterion in the design process of the civil engineering structures. A large number of factors that affect the occurrence of liquefaction during earthquake exist a form of uncertainty of non-statistical nature. Fuzzy systems are used to handle uncertainty from the data that cannot be handled by classical methods. It uses the fuzzy set to represent a suitable mathematical tool for modeling of imprecision and vagueness. The pattern classification of fuzzy classifiers provides a means to extract fuzzy rules for information mining that leads to comprehensible method for knowledge extraction from various information sources. Therefore, it is necessary to handle the soil liquefaction problem in a rational framework of fuzzy set theory. This study investigates the feasibility of using fuzzy comprehensive evaluation model for predicting soil liquefaction during earthquake. In the fuzzy comprehensive evaluation model of soil liquefaction, the following factors, such as earthquake intensity, standard penetration number, mean diameter and groundwater table, are selected as the evaluating indices. The results show that the method is a useful tool to assess the potential of soil liquefaction.

[1]  Xinhua Xue,et al.  Application of the adaptive neuro-fuzzy inference system for prediction of soil liquefaction , 2013, Natural Hazards.

[2]  K. T. Law,et al.  An energy approach for assessing seismic liquefaction potential , 1990 .

[3]  A. Goh.  Seismic liquefaction potential assessed by neural networks , 1994 .

[4]  Mahesh Pal,et al.  Support vector machines‐based modelling of seismic liquefaction potential , 2006 .

[5]  H. Bolton Seed,et al.  Evaluation of Liquefaction Potential Using Field Performance Data , 1983 .

[6]  G. Castro,et al.  On the Behavior of Soils During Earthquakes – Liquefaction , 1987 .

[7]  Youssef M A Hashash.  Special issue on biologically inspired and other novel computing techniques in geomechanics , 2007 .

[8]  Robert V. Whitman,et al.  Regression Models For Evaluating Liquefaction Probability , 1988 .

[9]  Ross W. Boulanger,et al.  Liquefaction at Moss Landing during Loma Prieta Earthquake , 1999 .

[10]  J. A. Sladen,et al.  The liquefaction of sands, a collapse surface approach , 1985 .

[11]  A. Goh,et al.  Support vector machines: Their use in geotechnical engineering as illustrated using seismic liquefaction data , 2007 .

[12]  Gokhan Saygili,et al.  Evaluation of liquefaction potential of soil deposits using artificial neural networks , 2007 .

[13]  Armen Der Kiureghian,et al.  STANDARD PENETRATION TEST-BASED PROBABILISTIC AND DETERMINISTIC ASSESSMENT OF SEISMIC SOIL LIQUEFACTION POTENTIAL , 2004 .

[14]  C. Kayadelen,et al.  Soil liquefaction modeling by Genetic Expression Programming and Neuro-Fuzzy , 2011, Expert Syst. Appl..

[15]  P. Robertson,et al.  Evaluating cyclic liquefaction potential using the cone penetration test , 1998 .

[16]  Thomas Oommen,et al.  Model Development and Validation for Intelligent Data Collection for Lateral Spread Displacements , 2010, J. Comput. Civ. Eng..

[17]  Thomas Oommen,et al.  Validation and Application of Empirical Liquefaction Models , 2010 .

[18]  Shuh-Gi Chern,et al.  CPT-BASED LIQUEFACTION ASSESSMENT BY USING FUZZY-NEURAL NETWORK , 2008 .

[19]  Orazio Giustolisi,et al.  Evaluation of liquefaction potential based on CPT results using evolutionary polynomial regression , 2010 .

[20]  I. M. Idriss,et al.  SIMPLIFIED PROCEDURE FOR EVALUATING SOIL LIQUEFACTION POTENTIAL , 1971 .

[21]  T. G. Sitharam,et al.  OCR Prediction Using Support Vector Machine Based on Piezocone Data , 2008 .

[22]  Ping-Sien Lin,et al.  Simplified cone penetration test-based method for evaluating liquefaction resistance of soils , 2003 .

[23]  Song Shuai.  Improvement and Application of Fuzzy Synthetic Evaluation of Groundwater Quality , 2009 .

[24]  Liu Ya-ping.  Determining the development potential of reservoirs at ultra-high water cut stage using comprehensive fuzzy analytical hierarchy evaluation method , 2009 .

[25]  L Ma,et al.  Fuzzy comprehensive evaluation method of F statistics weighting in identifying mine water inrush source , 2011 .