基于Fisher判别分析法的岩溶塌陷预测

为了更准确地预测岩溶塌陷,基于Fisher判别分析法,首先选择内聚力、内摩擦角、覆盖层厚度、覆盖层厚度减高水位埋深、覆盖层厚度减低水位埋深5个最主要的影响因素作为判别因子; 接着以桂林市20组岩溶塌陷案例为学习样本进行计算,建立相应的Fisher线性判别函数; 然后利用回代估计法对上述20组样本的预测结果进行逐一检验,其正确率为100%; 随后将上述预测结果与前人运用逐步判别、神经网络判别等方法得到的结果进行比较分析,认为Fisher判别分析法具有不需进行模型和参数的选择以及不受人为因素的影响等优点; 最后将建立的Fisher线性判别函数用于另外的10组实际案例进行预测分析,预测结果与实际情况完全吻合。结果表明:用Fisher判别分析法进行岩溶塌陷预测,简易方便,正确率高,实用性好; 该方法是岩溶塌陷预测的一种新方法。     

岩爆预测的Bayes判别模型及应用

基于Bayes判别法强大的判别分类能力,将Bayes判别理论应用到深部硬岩岩爆预测当中.选取最大切向应力σ_θ、单轴抗压强度σ_c、单轴抗拉强度σ_t和弹性能量指数W_(et)作为影响岩爆的因素,建立了以σ_θ/σ_c,σ_c/σ_t及W_(et)判别因子的岩爆预测的Bayes判别模型,以国内外15个深部岩体实例为训练样本进行训练,利用训练好的模型对灵宝东峪矿区、平煤集团八矿深部开拓巷道和铜陵冬瓜山深埋硬岩矿山岩爆进行预测.实例研究表明:该模型回判估计误判率为0,预测结果与工程实例实际岩爆情况相符合.     

砂土地震液化预测的Bayes判别模型及其应用

基于Bayes判别分析理论,在分析影响砂土液化因素的基础上,选取影响地震砂土液化因素的8个实测因子(地震烈度I、震中距L、地下水位dw、砂层埋藏深度ds、标贯击数N63.5、砂土颗粒平均粒径d50、不均匀系数Cu和剪应力比τd/σv)作为砂土地震液化判识指标,以唐山大地震中21组典型的砂土地震液化资料为学习样本,建立了唐山地区砂土地震液化预测的Bayes判别分析模型,并选用其他9组待检样本对判别模型进行验证。结果表明,Bayes判别分析模型预测性能良好,具有预测准确度高、回判估计的误判率低等特点,是解决砂土液化预测问题的有效方法之一。     

矿岩可爆性分级的距离判别方法及应用

矿岩可爆性的准确判定对采矿设计、安全生产等具有重要意义.将马氏距离判别法引入到矿岩可爆性分级中,建立了矿岩可爆性等级分类的距离判别模型.选用岩石抗压强度、岩石容重、岩石完整性系数和炸药单耗4项指标作为判别因子,将35个矿岩可爆性实例作为学习样本进行训练,建立了相应的判别函数对待判样本进行分类,结果表明经过训练后的模型误判率为零.将判别模型应用于工程实例,判别结果也与BP神经网络方法相符,表明该模型具有良好的判别功能,可以在实际工程中进行推广应用.     

Bayes判别分析法在泥石流预测中的应用研究

泥石流是山区典型的具有严重危害的地质灾害现象,若能实现对其提前预测预报将是十分有意义的.然而影响泥石流的因素错综复杂,本文综合考虑沟道纵比降、前期降水量、固体物质贮量三个必备因素对泥石流产生的影响,基于Bayes判别分析理论,利用泥石流资料作为训练样本,建立了泥石流预测的Bayes判别分析模型.预测结果表明,该模型结果与实际情况吻合良好,说明该模型在泥石流预测中具有良好的实用性和有效性.     

岩质边坡桥基形式判别函数

根据西南山区铁路岩质边坡桥基参数及边坡参数的调查资料,利用两组判别方法,获得桥基形式的判别函数,为岩质边坡桥基形式设计作指导.     

基于支持向量机的边坡垂直位移方向率预测及边坡稳定性研究

针对传统边坡位移量预测参数的局限和不足,以及在小样本下的预测参数估计区间较宽会导致工程设计偏于保守的问题,以垂直位移方向率作为边坡稳定性演化分析与评价的一个有效位移动力参数,提出支持向量机模型理论对其在相应周期内的发展趋势进行滚动预测估计,得到周期内垂直位移方向率的预测结果,通过与异常判据值对比得出边坡的稳定程度,并且以京新高速公路胶泥湾路段边坡的实际监测数据为实例进行验证分析。结果表明,预测数据与路基边坡实际情况基本吻合,因此垂直位移方向率可以作为公路边坡失稳判别的有效预测参数,同时支持向量机法评价垂直位移方向率参数对公路路基边坡进行预测预报具有一定的适用性和可靠性。     

基于BCABC-SVM的边坡稳定性预测

为了准确地对边坡稳定性进行预测,采用支持向量机(SVM)建立边坡稳定性和影响因素之间的非线性关系.针对支持向量机参数对预测效果的影响,采用基于细菌趋化的蜂群算法(BCABC)对其进行优化选择,提出了边坡稳定性预测的细菌趋化的蜂群优化支持向量机模型.运用该方法对边坡实例进行预测,预测结果与边坡稳定性实际状态相吻合,结果表明,基于细菌趋化的蜂群优化支持向量机模型在边坡稳定性评价中具有一定的可靠性和有效性.     

基于随机集理论的边坡稳定性评价方法

针对一类典型边坡,基于随机集理论提出了一种评价边坡稳定性的新方法,它可以有效解决边坡稳定性判别函数f的输入变量分别具有模糊性和随机性时,边坡稳定性判别的问题。首先,对于用不同模糊隶属度函数描述的输入变量φ,将这些模糊信息转化为由嵌套随机集表示的证据体,并利用Dempster组合规则得到将它们融合后的证据体;对于随机输入变量hw,也给出其随机集形式。然后,利用随机集扩展准则将随机集统一表示的两变量映射到输出,得到f输出的上下累积概率分布,用其判定边坡的稳定性。最后通过仿真验证了所提方法的有效性。     

基于响应面法的边坡稳定性预测

为对离子型稀土矿原地浸矿边坡稳定性进行预测,首先结合离子型稀土矿原地浸矿边坡特征,分别选取表土层和全风化矿层的重度、黏聚力、内摩擦角以及原地浸矿注液强度等7个因素进行正交实验.其次利用响应面法原理对正交实验结果进行分析,建立离子型稀土矿原地浸矿边坡稳定性分析模型,并将该模型应用与某稀土边坡实例,结果该模型对离子型稀土矿原地浸矿边坡稳定性预测精度高,且符合工程实例,说明了响应面法可应用于离子型稀土矿原地浸矿边坡稳定性分析.     

Over-excavation forecast of underground opening by using Bayes discriminant analysis method

A method to forecast the over-excavation of underground opening by using the Bayes discriminant analysis(BDA) theory was presented. The Bayes discriminant analysis theory was introduced. Based on an engineering example, the factors influencing the over-excavation of underground opening were taken into account to build a forecast BDA model, and the prior information about over-excavation of underground opening was also taken into consideration. Five parameters influencing the over-excavation of opening, including 2 groups of joints, 1 group of layer surface, extension and space between structure faces were selected as geometric parameters. Engineering data in an underground opening were used as the training samples. The cross-validation method was introduced to verify the stability of BDA model and the ratio of mistake-discrimination was equal to zero after the BDA model was trained. Data in an underground engineering were used to test the discriminant ability of BDA model. The results show that five forecast results are identical with the actual situation and BDA can be used in practical engineering.     

Bayesian discriminant analysis for prediction of coal and gas outbursts and application

Based on the principle of Bayesian discriminant analysis, we established a model of Bayesian discriminant analysis for predicting coal and gas outbursts. We selected five major indices which affect outbursts, i.e., initial speed of methane diffusion, a consistent coal coefficient, gas pressure, destructive style of coal and mining depth, as discriminating factors of the model. In our model, we divided the type of coal and gas outbursts into four grades regarded as four normal populations. We then obtained the corresponding discriminant functions through training a set of data from engineering examples as learning samples and evaluated their criteria by a back substitution method to verify the optimal properties of the model. Finally, we applied the model to the pre-diction of coal and gas outbursts in the Yunnan Enhong Mine. Our results coincided completely with the actual situation. These results show that a model of Bayesian discriminant analysis has excellent recognition performance, high prediction accuracy and a low error rate and is an effective method to predict coal and gas outbursts.     

Application of a support vector machine for prediction of slope stability

Slope stability estimation is an engineering problem that involves several parameters. To address these problems, a hybrid model based on the combination of support vector machine(SVM) and particle swarm optimization(PSO) is proposed in this study to improve the forecasting performance. PSO was employed in selecting the appropriate SVM parameters to enhance the forecasting accuracy. Several important parameters, including the magnitude of unit weight, cohesion, angle of internal friction, slope angle, height, pore water pressure coefficient, were used as the input parameters, while the status of slope was the output parameter. The results show that the PSO-SVM is a powerful computational tool that can be used to predict the slope stability.     

碎石土边坡稳定性及影响因素的数值模拟研究

结合工程实例,采用有限差分强度折减法对碎石土边坡进行稳定性数值模拟求得安全系数,并与传统分析方法进行计算比较.同时,分析边坡土性及计算模型参数对稳定性的影响.结果表明,FLAC3D分析边坡的稳定性可行且具有较好的优越性,内聚力、内摩擦角及土体密度对边坡稳定性的影响更加显著.     

岩质边坡稳定分析三维与二维的比较

提出岩质边坡沿软弱结构面滑移一剪切的三维稳定分析方法。在分析模型中,下滑体沿滑动面下滑,在其他的面上则产生剪切破坏。在结构面上满足莫尔库伦破坏准则,把剪切面上的摩阻力向下滑方向投影,由下滑体的力学平衡条件求解出未知力,通过迭代可以求得稳定系数。同时推导了摩阻力倾向与倾角的计算式,编制了相应的程序,并利用这个程序,研究了边坡长度、岩层与坡面夹角等因素对边坡稳定系数的影响,比较了三雏分析与二维分析的差别。     

基于时间序列的边坡位移实时预测方法

为了随时掌握边坡的变形情况,准确分析并预测边坡位移的变化趋势,确保边坡稳定可靠,基于时间序列方法,并结合以往的边坡位移监测数据,建立了边坡变形趋势的预测模型。提出了一种基于时间序列的边坡位移实时预测方法。以长春市地铁西客站监测为例,验证了本文方法的可行性。研究结果可以为边坡的稳定性分析提供一种新思路。     

基于改进Sarma法的倾倒变形体蓄水稳定性评价

库区强倾倒变形体常在蓄水期以特定模式发生失稳破坏。根据现场强倾倒变形体蓄水失稳特征,分析其破坏模式为"上拉下剪"式破坏,破坏面具有明显分段性。在传统Sarma法基础上,考虑饱和岩体强度降低及所受静水压力,通过调整岩层面强度折减系数改进了Sarma法。以Fortran为平台编写强倾倒变形体稳定性分析程序,通过苗尾水电站工程实例边坡对所提力学模型和分析方法进行验证,并与离散元模拟结果进行对比验证其准确性。最后进行参数分析,研究结果表明边坡自然坡角对倾倒变形体稳定性影响比较大,坡角越陡稳定性越低,同时软岩较多的边坡蓄水后稳定性将大大降低,得出的结论和规律符合工程实际。     

Multi-factor sensitivity analysis of shallow unsaturated clay slope stability

An unsaturated clay slope, with various sloping angles and a thickness of 14 m, consists of backfill, slope soil and residual soil. Slide interfaces were determined by geophysical approaches and the original slope was reconstructed. Sub-slope masses were classified based on the varieties of sloping angle. A force recursive principle was proposed to calculate the stability coefficient of the sub-slope masses. The influencing factors such as sloping angle, water content, hydrostatic pressure, seismic force as well as train load were analyzed. The range and correlation of the above-mentioned factors were discussed and coupled wave equations were established to reflect the relationships between unit weight, cohesion, internal frictional angle, and water content, as well as between internal frictional angle and cohesion. The sensitivity analysis of slope stability was carried out and susceptive factors were determined when the factors were taken as independent and dependent variables respectively. The results show that sloping angle, water content and earthquake are the principal susceptive factors influencing slope stability. The impact of hydrostatic pressure on slope stability is similar to the seismic force in quantity. Train load plays a small role in slope stability and its influencing only reaches the roadbed and its neighboring slope segment. If the factors are taken as independent variables, the influencing extent of water content and cohesion on slope stability can be weakened and train load can be magnified.