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1976年唐山地震期间,附近一些地区出现了砂土液化现象。本文根据工程勘探中的实例及实验数据,进行了砂土液化作用的统计和综合预测。文章中采用贝叶斯准则下的逐步判别分析方法,对唐山地区已知液化地点和非液化地点,作了五种检验计算,挑选出准确度及可靠性最高的变量模式。从而,对于当地震为Ⅷ度烈度时的砂土液化进行了预测。五种预测结果相同,互相印证,可靠性高,分组最大后验概率大多在0.99以上。在此条件下,外推预测结果可信。工程实践中,迫切需要对砂土液化进行综合性预测,而一般采用地质学或试验方法,仅能对砂土液化作单因素或少量因素下的预测,本文提出了综合性的通用预测方法,为砂土液化统计预测提供了新途径。砂土液化是平原地区的一种重要地震灾害。国内外多次大地震中,都曾因饱水砂土受到地震作用,引起孔隙水压增高及砂粒间的结合力和摩擦力降低,而使砂层发生液化状态的流动,并伴随有地基承载能力降低或失效。1964年以来,新潟地震及阿拉斯加地震时,由砂土液化造成了罕见的灾害。激发了各国、尤其是美国和日本对砂土液化预测的研究。但还多是单因素或少量因素影响下的分析方法。未能进行综合分析及推断。采用数理统计方法,可以综合分析影响砂土液化的各因素的数字特征。本文采用了一种贝叶斯(Be
During the Tangshan earthquake in 1976, sand liquefaction occurred in some areas nearby. Based on the examples and experimental data in engineering exploration, the paper makes statistics and synthetical prediction of sand liquefaction. In this paper, a Bayesian discriminant analysis method is used to calculate and test five known liquefaction sites and non-liquefied sites in Tangshan area. The variables with the highest accuracy and reliability are selected. Therefore, the prediction of sand liquefaction when the earthquake is Ⅷ intensity is predicted. The five kinds of prediction results are the same, confirming each other, and the reliability is high, and the maximum posterior probability of the grouping is mostly above 0.99. Under this condition, the extrapolation predictions are credible. In engineering practice, there is an urgent need to make a comprehensive prediction of sand liquefaction. Generally, geology or test methods are used to predict sand liquefaction only under single or small factors. In this paper, a general and general prediction method is proposed, It provides a new way for the statistical prediction of sand liquefaction. Sand liquefaction is an important earthquake disaster in the plain area. In many large earthquakes both at home and abroad, earthquakes have been caused by saturated sands, causing the increase of pore water pressure and the decrease of the binding force and friction force between sands, resulting in the liquefaction of the sand bed. Decreased ability or failure. Since 1964, the Niigata earthquake and the Alaskan earthquake have caused rare disasters caused by sand liquefaction. All countries, especially the United States and Japan, have been stimulated to study the prediction of sand liquefaction. But more than one factor or a few factors under the influence of the analysis. Failed to conduct a comprehensive analysis and inference. Mathematical statistics can be used to comprehensively analyze the digital characteristics of various factors affecting sand liquefaction. This article uses a Bayesian (Be