【摘要】 为了充分考虑影响砂土液化的多种因素,选取不同的参数组合,建立不同的砂土液化判别BP神经网络模型,编写了饱和砂土液化判别BP神经网络程序SLV,并根据现场实测资料进行计算和分析.结果表明,地震作用是液化的直接原因,砂土处于饱和状态是液化的前提条件,影响液化的主要因素包括标准贯入锤击数、砂土不均匀系数以及地震剪应力比.文中建立的BP神经网络模型具有高度的分类和识别能力,可用于评估砂土液化的影响因素.更多还原

【Abstract】 In order to investigate various factors to affect the liquefaction of sandy soil,different BP neural network models for liquefaction evaluation were established based on different combinations of the input neurons.A BP neural network-based program,namely SLV,was then presented for the liquefaction evaluation of saturated sandy soil.Some comparison analyses were finally carried out according to the results of field observation.It is shown that the earthquake action is a direct cause of the liquefaction,that the saturation state of sandy soil is the precondition of the liquefaction,and that the standard penetration blow-count,the non-uniformity coefficient and the shearing stress ratio are the main influencing factors of the liquefaction.Moreover,it is indicated that the proposed BP neural network model can effectively evaluate the factors to affect the liquefaction of sandy soil due to its strong classifying and distinguishing ability.更多还原