砂土液化预测的Fisher判别模型及应用
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摘要
基于Fisher判别理论建立了砂土液化可能性的Fisher判别分析(FDA)模型。在分析砂土液化影响因素的基础上,选取烈度、震中距、地下水位、砂层埋深、标贯击数、平均粒径、不均匀系数、剪应力比等8个实测特征指标作为FDA模型的预测指标。利用砂土液化的实测数据作为训练样本进行训练,建立FDA模型对砂土液化进行预测,并用其他未参加训练的实测数据进行了验证。研究结果表明,FDA模型简便可行、预测精度高,是解决砂土液化预测问题的有效方法之一。
Based on Fisher discriminant theory,the Fisher discriminant analysis(FDA) model was established for forecasting the possibility of sand liquefaction.Eight factors were selected such as seismic intensity,epicenteral distance,groundwater level,sand depth,blow number of standard penetration test,mean granular diameter,coefficient of nonuniformity,ratio of shearing stress to effective overburden stress as the discriminant factors of the FDA model.A series of experimental data of sand liquefaction were taken as the training and testing samples,then some other practical data were used to verify this model.The results show that the FDA model is a simple,feasible and high accurate prediction method;and it is one of the efficient methods for solving prediction of sand liquefaction.
Based on Fisher discriminant theory,the Fisher discriminant analysis(FDA) model was established for forecasting the possibility of sand liquefaction.Eight factors were selected such as seismic intensity,epicenteral distance,groundwater level,sand depth,blow number of standard penetration test,mean granular diameter,coefficient of nonuniformity,ratio of shearing stress to effective overburden stress as the discriminant factors of the FDA model.A series of experimental data of sand liquefaction were taken as the training and testing samples,then some other practical data were used to verify this model.The results show that the FDA model is a simple,feasible and high accurate prediction method;and it is one of the efficient methods for solving prediction of sand liquefaction.
引文
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[2]SEED H B,IDRISS I M.Simplified procedures for evaluating soil liquefaction potential[J].Journal of Soil Mechanics and Foundation Division,ASCE,1971,97(9):1249-1273.
[3]中华人民共和国建设部.GB50011-2001建筑抗震设计规范[S].北京:中国建筑工业出版社,2001.
[4]唐世栋,罗立疆,林华国.国内外砂土液化判别方法的比较[J].工程勘察,2007,(4):3-6.TANG Shi-dong,LUO Li-jiang,LIN Hua-guo.Comparison of discrimination method for sand liquefaction at home and abroad[J].Geotechnical Investigation&Surveying,2007,(4):3-6.
[5]JUANG C H,JIANG T,ANDRUS R D.Assessing probability-based methods for liquefaction potential evaluation[J].Journal of Geotechnical and Geoenvi-ronmental Engineering,2002,128(7):580-589.
[6]刘章军,叶燎原,彭刚.砂土地震液化的模糊概率评判方法[J].岩土力学,2008,29(4):876-880.LIU Zhang-jun,YE Liao-yuan,PENG Gang.Fuzzy probability comprehensive evaluation method for sand liquefaction during earthquake[J].Rock and Soil Mechanics,2008,29(4):876-880.
[7]潘建平,孔宪京,邹德高.基于Logistic回归模型的砂土液化概率评价[J].岩土力学,2008,29(9):2567-2571.PAN Jian-ping,KONG Xian-jing,ZOU De-gao.Probabilistic evaluation of sand liquefaction based on Logistic regression model[J].Rock and Soil Mechanics,2008,29(9):2567-2571.
[8]LAI S Y,CHANG W J,LIN P S.Logistic regression model for evaluating soil liquefaction probability using CPT data[J].Journal of Geotechnical and Geo-environmental Engineering,2006,132(6):694-704.
[9]REZANIA M,JAVADI A A.A new genetic programming model for predicting settlement of shallow foundations[J].Can.Geotech.J.,2007,44(12):1462-1473.
[10]MOHAMMAD R,AKBAR A J,ORAZIO G.Evaluation of liquefaction potential based on CPT results using evolutionary polynomial regression[J].Computers and Geotechnics,2010,37:82-92.
[11]刘红军,薛新华.砂土地震液化预测的人工神经网络模型[J].岩土力学,2004,25(12):1942-1946.LIU Hong-jun,XUE Xin-hua.Artificial neural network model for prediction of seismic liquefaction of sand soil[J].Rock and Soil Mechanics,2004,25(12):1942-1946.
[12]ADEL M H,DERIN U.Neural network model for liquefaction potential in soil deposits using Turkey and Taiwan earthquake data[J].Soil Dynamics and Earthquake Engineering,2007,27:521-540.
[13]HANNA A M,URAL D N,SAYGILI G.Evaluation of liquefaction potential of soil deposits using artificial neural networks[J].J.Eng.Comput.,2007,24(1):5-16.
[14]夏建中,罗战友,龚晓南,等.基于支持向量机的砂土液化预测模型[J].岩石力学与工程学报,2005,24(22):4139-4144.XIA Jian-zhong,LUO Zhan-you,GONG Xiao-nan,et al.Support vector machine for predicting sand lique-faction[J].Chinese Journal of Rock Mechanics and Engineering,2005,24(22):4139-4144.
[15]邰淑彩,孙韫玉,何娟娟.应用数理统计[M].武汉:武汉大学出版社,2005:105-132.
[16]白云飞,邓建,董陇军,等.深部硬岩岩爆预测的FDA模型及其应用[J].中南大学学报(自然科学版),2009,40(5):1417-1421.BAI Yun-fei,DENG Jian,DONG Long-jun,et al.Fisher discriminant analysis model of rock burst prediction and its application in deep hard rock engineering[J].Journal of Central South University:Science and Technology,2009,40(5):1417-1421.
[17]杨健,陈庆寿.砂土液化影响因素及其判别方法[J].西部探矿工程,2004,93(2):1-2.YANG Jian,CHEN Qing-shou.Affecting factors and distinguishing methods of sandy soil liquefaction[J].West-China Exploration Engineering,2004,93(2):1-2.
[18]金志仁.基于距离判别分析方法的砂土液化预测模型及应用[J].岩土工程学报,2008,30(5):776-780.JIN Zhi-ren.Prediction of sand liquefaction based on distance discriminant analysis and its application[J].Chinese Journal of Geotechnical Engineering,2008,30(5):776-780.
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