共查询到20条相似文献，搜索用时 55 毫秒
1.
为利用水文现象相似性和极限学习机(ELM)集成学习提高洪水预报精度,提出了一种基于相似度匹配的集成ELM洪水预报方法(SM-ELM)。方法首先从多个ELM模型中,为每一个训练样本找到最优的ELM模型,然后从训练集中,为测试样本匹配出最相似的前k个训练样本,最后利用这k个训练样本分别对应的最优ELM模型,对测试样本采用加权平均法进行集成预报。为证明提出方法的可行性和有效性,以昌化流域的历史洪水为例进行了验证。结果表明,相对于单个ELM,集成ELM模型能有效地提高预测精度。从均方根误差上看,集成ELM模型性能比单个ELM模型提升了10%~15%。在三种集成方法中,SM-ELM能够以较少的模型数量获得较高且稳定的预报精度。 相似文献
2.
Deep excavations particularly in deep deposits of soft clay can cause excessive ground movements and result in damage to adjacent buildings. Extensive plane strain finite element analyses considering the small strain effect have been carried out to examine the wall deflections for excavations in soft clay deposits supported by retaining walls and bracing. The excavation geometry, soil strength and stiffness properties, and the wall stiffness were varied to study the wall deflection behavior. Based on these results, a simple Polynomial Regression (PR) model was developed for estimating the maximum wall deflection. Wall deflections computed by this method compare favorably with a number of field and published records. 相似文献
3.
In this paper, we propose multilevel Monte Carlo (MLMC) methods that use ensemble level mixed multiscale methods in the simulations of multiphase flow and transport. The contribution of this paper is twofold: (1) a design of ensemble level mixed multiscale finite element methods and (2) a novel use of mixed multiscale finite element methods within multilevel Monte Carlo techniques to speed up the computations. The main idea of ensemble level multiscale methods is to construct local multiscale basis functions that can be used for any member of the ensemble. In this paper, we consider two ensemble level mixed multiscale finite element methods: (1) the no-local-solve-online ensemble level method (NLSO); and (2) the local-solve-online ensemble level method (LSO). The first approach was proposed in Aarnes and Efendiev (SIAM J. Sci. Comput. 30(5):2319-2339, 2008) while the second approach is new. Both mixed multiscale methods use a number of snapshots of the permeability media in generating multiscale basis functions. As a result, in the off-line stage, we construct multiple basis functions for each coarse region where basis functions correspond to different realizations. In the no-local-solve-online ensemble level method, one uses the whole set of precomputed basis functions to approximate the solution for an arbitrary realization. In the local-solve-online ensemble level method, one uses the precomputed functions to construct a multiscale basis for a particular realization. With this basis, the solution corresponding to this particular realization is approximated in LSO mixed multiscale finite element method (MsFEM). In both approaches, the accuracy of the method is related to the number of snapshots computed based on different realizations that one uses to precompute a multiscale basis. In this paper, ensemble level multiscale methods are used in multilevel Monte Carlo methods (Giles 2008a, Oper.Res. 56(3):607-617, b). In multilevel Monte Carlo methods, more accurate (and expensive) forward simulations are run with fewer samples, while less accurate (and inexpensive) forward simulations are run with a larger number of samples. Selecting the number of expensive and inexpensive simulations based on the number of coarse degrees of freedom, one can show that MLMC methods can provide better accuracy at the same cost as Monte Carlo (MC) methods. The main objective of the paper is twofold. First, we would like to compare NLSO and LSO mixed MsFEMs. Further, we use both approaches in the context of MLMC to speedup MC calculations. 相似文献
4.
Accurate assessment of undrained shear strength(USS)for soft sensitive clays is a great concern in geotechnical engineering practice.This study applies novel data-driven extreme gradient boosting(XGBoost)and random forest(RF)ensemble learning methods for capturing the relationships between the USS and various basic soil parameters.Based on the soil data sets from TC304 database,a general approach is developed to predict the USS of soft clays using the two machine learning methods above,where five feature variables including the preconsolidation stress(PS),vertical effective stress(VES),liquid limit(LL),plastic limit(PL)and natural water content(W)are adopted.To reduce the dependence on the rule of thumb and inefficient brute-force search,the Bayesian optimization method is applied to determine the appropriate model hyper-parameters of both XGBoost and RF.The developed models are comprehensively compared with three comparison machine learning methods and two transformation models with respect to predictive accuracy and robustness under 5-fold cross-validation(CV).It is shown that XGBoost-based and RF-based methods outperform these approaches.Besides,the XGBoostbased model provides feature importance ranks,which makes it a promising tool in the prediction of geotechnical parameters and enhances the interpretability of model. 相似文献
5.
《地学前缘(英文版)》2020,11(4):1095-1106
Soft computing techniques are becoming even more popular and particularly amenable to model the complex behaviors of most geotechnical engineering systems since they have demonstrated superior predictive capacity,compared to the traditional methods.This paper presents an overview of some soft computing techniques as well as their applications in underground excavations.A case study is adopted to compare the predictive performances of soft computing techniques including eXtreme Gradient Boosting(XGBoost),Multivariate Adaptive Regression Splines(MARS),Artificial Neural Networks(ANN),and Support Vector Machine(SVM) in estimating the maximum lateral wall deflection induced by braced excavation.This study also discusses the merits and the limitations of some soft computing techniques,compared with the conventional approaches available. 相似文献
6.
齿坎式挡土结构物极限抗滑力研究 总被引：1，自引：1，他引：0
以齿坎式挡土结构物的现场抗滑试验为依据,运用非线性弹性有限元方法,对齿坎长度分别为0、0.7 m和1.0 m的挡土结构物的现场试验进行了理论分析,研究了位于软弱地基中的挡土结构物中的齿坎抗滑机制,其有限元理论分析能很好地表征现场试验成果,并运用强度折减的有限元方法对齿坎式挡土结构物进行极限设计,该理论研究可为工程设计提供齿坎抗滑作用的设计理论。 相似文献
7.
Zhongqiang Liu Graham Gilbert Jose Mauricio Cepeda Asgeir Olaf Kydland Lysdahl Luca Piciullo Heidi Hefre Suzanne Lacasse 《地学前缘(英文版)》2021,12(1):385-393
This paper introduces three machine learning(ML)algorithms,the‘ensemble'Random Forest(RF),the‘ensemble'Gradient Boosted Regression Tree(GBRT)and the Multi Layer Perceptron neural network(MLP)and applies them to the spatial modelling of shallow landslides near Kvam in Norway.In the development of the ML models,a total of 11 significant landslide controlling factors were selected.The controlling factors relate to the geomorphology,geology,geo-environment and anthropogenic effects:slope angle,aspect,plan curvature,profile curvature,flow accumulation,flow direction,distance to rivers,water content,saturation,rainfall and distance to roads.It is observed that slope angle was the most significant controlling factor in the ML analyses.The performance of the three ML models was evaluated quantitatively based on the Receiver Operating Characteristic(ROC)analysis.The results show that the‘ensemble'GBRT machine learning model yielded the most promising results for the spatial prediction of shallow landslides,with a 95%probability of landslide detection and 87%prediction efficiency. 相似文献
8.
为准确评估软土地区基坑施工安全以及对周围环境的影响,开挖过程中的时间和空间影响因素不可忽视。以长江漫滩软土地区某深基坑开挖工程为依托,首先建立考虑顺逆结合施工过程的有限元模型,将地连墙水平位移的计算值与实测值进行对比,验证有限元计算的可靠性;基于理论分析、数值计算和实测数据,采用坑角效应影响系数和等效水平抗力系数来衡量时空效应对支护变形的影响,提出考虑时空效应的地连墙变形计算方法;通过工程实例验证了在软土地区基坑设计计算中考虑时空效应的必要性以及所提计算方法的合理性。该研究成果可为软土地区深基坑变形计算提供有益借鉴。 相似文献
9.
The influence of the consolidation on a strutted excavation in soft soil is analysed using a computer code based on the finite element method. A base jet-grout slab is considered in order to improve stability against bottom heave failure and minimize wall displacements. The numerical model incorporates the Biot consolidation theory (coupled formulation of the flow and equilibrium equations) with soil constitutive relations simulated by the p–q–θ critical state model. Special emphasis is given to the analysis, during and after the construction period, of the pore pressures, shear stresses, stress levels and displacements in the ground, as well as strut compression loads, wall displacements and bending moments, earth pressures on the wall faces and compression loads and bending moments on the jet-grout slab. The safety factor against bottom heave is also evaluated from the finite element analysis considering formulations of the critical state soil mechanics, and also compared to values obtained with traditional methods that use limit equilibrium approach and bearing capacity fundamentals. 相似文献
10.
The compression index (Cc) is a necessary parameter for the settlement calculation of clays. However, determination of the compression index from oedometer tests takes a relatively long time and leads to a very demanding experimental working program in the laboratory. Therefore, geotechnical engineering literature involves many studies based on indirect methods such as multiple regression analysis (MLR) and soft computing methods to determine the compression index. This study is aimed to predict the compression index by using extreme learning machine (ELM), Bayesian regularization neural network (BRNN), and support vector machine (SVM) methods. The selected variables for each method are the natural water content (wn), initial void ratio (e0), liquid limit (LL), and plasticity index (PI) of clay samples. Many trials were carried out in order to get the best prediction performance with each model. The application results obtained from the models were also compared based on the correlation coefficient (R), coefficient of efficiency (E), and mean squared error (MSE). The results indicate that the BRNN method has better success on estimation of the compression index compared to the ELM and SVM methods. 相似文献
11.
Binh Thai Pham Dieu Tien Bui Indra Prakash 《Geotechnical and Geological Engineering》2017,35(6):2597-2611
In this study, we have evaluated and compared prediction capability of Bagging Ensemble Based Alternating Decision Trees (BADT), Logistic Regression (LR), and J48 Decision Trees (J48DT) for landslide susceptibility mapping at part of the Uttarakhand State (India). The BADT method has been proposed in the present study which is a novel hybrid machine learning ensemble approach of bagging ensemble and alternating decision trees. The J48DT is a relative new machine learning technique which has been applied only in few landslide studies, and the LR is known as a popular landslide susceptibility model. For the model studies, a spatial database of 930 historical landslide events and 15 landslide affecting factors have been collected and analyzed. This database has been used to build and validate the landslide models namely BADT, LR and J48DT Predictive capability of these models has been validated and compared using statistical analyzing methods and Receiver Operating Characteristic (ROC) curve. Results show that these three landslide models (BADT, LR and J48DT) performed well with the training dataset. However, using the validation dataset the BADT model has the highest prediction capability, followed by the LR model, and the J48DT model, respectively. This indicates that the BADT is a promising method which can be used for landslide susceptibility assessment also for other landslide prone areas. 相似文献
12.
D. T. BergadoJ. C. ChaiN. Miura 《Computers and Geotechnics》1995,17(4):447-471
The behavior of a reinforced embankment on soft Bangkok clay has been analyzed by plane strain finite element method. The finite element analysis considers the selection of proper soil/reinforcement properties according to the relative displacement pattern of upper and lower interface elements. The large deformation phenomenon is simulated by updating the node coordinates, including those of the embankment elements above the current construction level, which ensures that the applied fill thickness simulates the actual field value. A full scale test reinforced embankment with a vertical face (wall) on Bangkok clay has been analyzed by the proposed finite element method, and the numerical results are compared with the field data. The response of a reinforced embankment on soft ground is principally controlled by the interaction between the reinforced soil mass and soft ground and the interaction between the grid reinforcement and the backfill soil. The tension in reinforcement and lateral displacement of the wall face varied during consolidation of foundation soil. The maximum tension force occurred in the reinforcement layer placed at the base of reinforced mass, due to bending of the reinforced mass resulting from differential settlements. It is considered necessary to account for the permeability variation of the soft ground foundation in the finite element analysis. 相似文献
13.
We study and compare five different combinations of finite element spaces for approximating the coupled flow and solid deformation system, so-called Biot’s equations. The permeability and porosity fields are heterogeneous and depend on solid displacement and fluid pressure. We provide detailed comparisons among the continuous Galerkin, discontinuous Galerkin, enriched Galerkin, and two types of mixed finite element methods. Several advantages and disadvantages for each of the above techniques are investigated by comparing local mass conservation properties, the accuracy of the flux approximation, number of degrees of freedom (DOF), and wall and CPU times. Three-field formulation methods with fluid velocity as an additional primary variable generally require a larger number of DOF, longer wall and CPU times, and a greater number of iterations in the linear solver in order to converge. The two-field formulation, a combination of continuous and enriched Galerkin function space, requires the fewest DOF among the methods that conserve local mass. Moreover, our results illustrate that three out of the five methods conserve local mass and produce similar flux approximations when conductivity alteration is included. These comparisons of the key performance indicators of different combinations of finite element methods can be utilized to choose the preferred method based on the required accuracy and the available computational resources.
相似文献14.
采用有限单元法研究了影响软土地区地下连续墙最大侧向变形的主要参数。针对基坑开挖深度H、基坑开挖宽度B、单位宽度地下连续墙系统刚度S、支撑结构的轴向刚度 及黏土归一化的不排水抗剪强度 为不排水抗剪强度, 为有效垂直应力）5个参数进行分析研究,通过回归分析研究结果,给出地下连续墙最大侧向变形的简易计算方法。利用简易计算方法,计算实际工程中基坑案例的地下连续墙最大侧向变形,并与现场监测结果进行对比,验证了计算方法的准确性,可为以后预估地下连续墙最大侧向变形及检查设计提供参考。 相似文献
15.
This paper presents a novel strut-free earth retaining wall system for excavation in soft clay, referred to as the rigid and fixed diaphragm (RFD) wall retaining system. The RFD system is comprised of four main structures—diaphragm walls, rib-walls, cross walls, and buttress walls—and a complementary structure—the cap-slab. The characteristics of the RFD system are: (1) the formation of a continuous earth retaining wall by constructing diaphragm walls along the circumference of the excavated zone; (2) the formation of a rigid and fixed retaining wall system by a series of rib-walls and cross walls; and (3) the formation of a rigid retaining wall by buttress walls and the cap-slab. Furthermore, the performance and mechanisms of the RFD system were investigated carefully through three-dimensional finite element analyses. The results demonstrated that the system stiffness of the RFD system was a major factor controlling deformations induced by excavation. Moreover, the excavation geometry determined the dimension of each component of the RFD system.
相似文献16.
Columnar inclusion is one of the effective and widely used methods for improving the engineering properties of soft clay ground. This article investigates the consolidation behavior of composite soft clay ground using both physical model tests under an axial-symmetry condition and finite element simulations using the PLAXIS 2D program. It was determined that the final settlement and the rate of consolidation of the composite ground depended on the stress state. For an applied stress that is much lower than the failure stress, the final settlement of the composite ground was lower, and the consolidation was rapid. When the soil–cement column failed, the stress on the column suddenly decreased (due to strain-softening); meanwhile, the stress on the soil increased to maintain the force equilibrium. Consequently, the excess pore pressure in the surrounding clay increased immediately. The cracked soil–cement column acted as a drain, which accelerated the dissipation of the excess pore pressure. The consolidation of the composite ground was mainly observed in the vertical direction and was controlled by the area ratio, which is the ratio of the diameter of the soil–cement column to the diameter of the composite ground, a. The stress on the column was shown to be low for a composite ground with a high value of a, which resulted in less settlement and fast consolidation. For a long soil–cement column, the excess pore pressures in the surrounding clay and the column were essentially the same at a given consolidation time throughout the improvement depth. It is proposed that the soil–cement column and surrounding clay form a compressible ground, and the consolidation occurs in the vertical direction. The composite coefficient of consolidation (cv(com)) that was obtained from the physical model test on the composite ground can be used to approximate the rate of consolidation. This approximation was validated via a finite element simulation. The proposed method is highly useful to geotechnical engineers because of its simplicity and reliable prediction. 相似文献
17.
Summary Pseudo-static and dynamic non-linear finite element analyses have been performed to assess the dynamic behaviour of gravity retaining walls subjected to horizontal earthquake loading. In the pseudo-static analysis, the peak ground acceleration is converted into a pseudo-static inertia force and applied as a horizontal incremental gravity load. In the dynamic analysis, an actual measured earthquake acceleration time history has been scaled to provide peak ground acceleration values of 0.1 g and 0.3 g. Good agreement is obtained between the pseudo-static analysis and analytical methods for the calculation of the active coefficient of earth pressure. However, the results from the dynamic analysis require careful interpretation. In the pseudo-static analysis, the increase in the point of application of the resultant active force with the horizontal earthquake coefficient k
h from the one-third point to the mid-height of the wall is clearly observed. In the dynamic analysis, the variation in the point of application is shown to be a function of the type of wall deformation. Both finite element analyses indicate the importance of determining the magnitude of the predicted displacements when assessing the behaviour of the wall to seismic loading. 相似文献
18.
V. Six H. Mroueh I. Shahrour M. Bouassida 《Geotechnical and Geological Engineering》2012,30(4):813-825
This paper deals with the influence of the earth pressure at rest coefficient K 0 on stone columns behavior. This parameter is related to the initial stresses caused by the compression of in situ soil and by the installation (expansion of column material). Numerical calculations based on finite element method are compared to analytical methods and conventional engineering methods addressed to the design of stone columns. The presented results led to a better comprehension of previous methods for the design of stone column and highlighted the importance of well defining the initial stress level due to stone columns installation. 相似文献
19.
《地学前缘(英文版)》2022,13(2):101313
Deep excavation during the construction of underground systems can cause movement on the ground, especially in soft clay layers. At high levels, excessive ground movements can lead to severe damage to adjacent structures. In this study, finite element analyses (FEM) and the hardening small strain (HSS) model were performed to investigate the deflection of the diaphragm wall in the soft clay layer induced by braced excavations. Different geometric and mechanical properties of the wall were investigated to study the deflection behavior of the wall in soft clays. Accordingly, 1090 hypothetical cases were surveyed and simulated based on the HSS model and FEM to evaluate the wall deflection behavior. The results were then used to develop an intelligent model for predicting wall deflection using the functional linked neural network (FLNN) with different functional expansions and activation functions. Although the FLNN is a novel approach to predict wall deflection; however, in order to improve the accuracy of the FLNN model in predicting wall deflection, three swarm-based optimization algorithms, such as artificial bee colony (ABC), Harris’s hawk’s optimization (HHO), and hunger games search (HGS), were hybridized to the FLNN model to generate three novel intelligent models, namely ABC-FLNN, HHO-FLNN, HGS-FLNN. The results of the hybrid models were then compared with the basic FLNN and MLP models. They revealed that FLNN is a good solution for predicting wall deflection, and the application of different functional expansions and activation functions has a significant effect on the outcome predictions of the wall deflection. It is remarkably interesting that the performance of the FLNN model was better than the MLP model with a mean absolute error (MAE) of 19.971, root-mean-squared error (RMSE) of 24.574, and determination coefficient (R2) of 0.878. Meanwhile, the performance of the MLP model only obtained an MAE of 20.321, RMSE of 27.091, and R2 of 0.851. Furthermore, the results also indicated that the proposed hybrid models, i.e., ABC-FLNN, HHO-FLNN, HGS-FLNN, yielded more superior performances than those of the FLNN and MLP models in terms of the prediction of deflection behavior of diaphragm walls with an MAE in the range of 11.877 to 12.239, RMSE in the range of 15.821 to 16.045, and R2 in the range of 0.949 to 0.951. They can be used as an alternative tool to simulate diaphragm wall deflections under different conditions with a high degree of accuracy. 相似文献