【摘要】 为了给砂土地震液化的数量化研究提供参考,基于多元统计分析理论,建立砂土地震液化判别与液化势分类的Bayes判别分析模型。模型选用震级、地面加速度最大值、标准贯入击数、比贯入阻力、相对密实度、平均粒径和地下水位等7个指标作为判别因子;将砂土液化势分为严重液化、中等液化、轻微液化和未液化4个级别,并作为Bayes判别分析的4个正态总体;以17个砂土实测数据作为训练样本,建立Bayes线性判别函数,以Bayes线性判别函数的最大值对应的总体作为样品所归属的总体;最后将建立的模型对训练样本进行回判,以回代估计误判率对模型进行检验。研究表明,对训练样本的回代误判率为0,对另外20个砂土样本的判别正确率为90%。更多还原

【Abstract】 To provide reference for the quantitative study on seismic liquefaction of sandy soil,Bayes discriminant model(BDM)for identification and classification of seismic liquefaction potential of sandy soil was established based on multivariate statistical analysis theory.According to the analysis of some influencing factors of sand liquefaction,seven parameters including earthquake magnitude,peak ground acceleration,the value of standard penetration test,specific penetration resistance,relative compaction,mean particle diameter,and underground water table were selected as the indexes for synthetic evaluation of the seismic liquefaction of sandy soil.The seismic liquefaction potential of sandy soil was divided into four grades,i.e.,serious liquefaction,medium liquefaction,slight liquefaction and non-liquefaction,and regarded as four normal collectivities in Bayes discriminant analysis.Bayes discriminant functions obtained through training 17 sandy soil samples were employed to compute the Bayes function values of samples,and the maximal function value was used to judge which collectivity the sample belongs to.The established Bayes discriminant analysis model was used to back-discriminate the training samples,and verified by the ratio of mistake-discrimination.The study indicates that the ratio of mistake-discrimination of training samples is zero.The other twenty sets of sand samples regarded as testing samples were assessed by BDM and the correct rate is 90%.更多还原