Uplift capacity of suction caisson in clay using multivariate adaptive regression spline

Pijush Samui; Sarat Das; Dookie Kim

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Uplift capacity of suction caisson in clay using multivariate adaptive regression spline

机译：基于多元自适应回归样条的黏土沉井提升能力

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This study adopts Multivariate Adaptive Regression Spline (MARS) model for determination of uplift capacity (Q) of suction caisson in clay. MARS is a non-parametric adaptive regression procedure. The model inputs included the Ljd (L is the embedded length of the caisson and d is the diameter of caisson), undrained shear strength of soil at the depth of the caisson tip (su), D/L (D is the depth of the load application point from the soil surface), inclined angle (0) and load rate parameter (Tk). The output of MARS is Q, The results of MARS are compared with Artificial Neural Network (ANN) and Finite Element Method (FEM). An equation has been presented from the developed MARS. The results show the strong potential of MARS to be applied to uplift capacity of suction caisson in clay.

机译：本研究采用多元自适应回归样条（MARS）模型确定黏土中沉井的提水能力（Q）。 MARS是一种非参数自适应回归程序。模型输入包括Ljd（L是沉箱的嵌入长度，d是沉箱的直径），沉箱尖端深度（su）上土壤的不排水抗剪强度，D / L（D是沉箱深度）。从土壤表面施加的载荷点），倾斜角（0）和载荷率参数（Tk）。 MARS的输出为Q。将MARS的结果与人工神经网络（ANN）和有限元方法（FEM）进行比较。从已开发的MARS中提出了一个方程。结果表明，MARS具有很强的潜力，可用于黏土中沉井的提升能力。

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来源
《Ocean Engineering》 |2011年第18期|p.2123-2127|共5页
作者
Pijush Samui; Sarat Das; Dookie Kim;
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作者单位

Centre for Disaster Mitigation and Management, VIT University, Vellore 632014, India;

Department of Civil Engineering, National Institute of Technology, Rourkela 769008, India;

Department of Civil Engineering, Kunsan National University, Kunsan, Jeonbuk, South Korea;

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原文格式 PDF
正文语种 eng
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关键词
uplift capacity; multivariate adaptive regression spline; caisson; artificial neural network;

机译：提升能力多元自适应回归样条;藻井;人工神经网络;

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专利

1. Determination of Uplift Capacity of Suction Caisson Using Gaussian Process Regression, Minimax Probability Machine Regression and Extreme Learning Machine [J] . Samui Pijush, Kim Dookie, Jagan J., Iranian Journal of Science and Technology, Transactions of Civil Engineering . 2019,第JULaSUPPLa1期

机译：使用高斯过程回归，极小概率机回归和极限学习机确定吸水沉井的提升能力
2. Determination of Uplift Capacity of Suction Caisson Using Gaussian Process Regression, Minimax Probability Machine Regression and Extreme Learning Machine [J] . Samui Pijush, Kim Dookie, Jagan J., Iranian Journal of Science and Technology, Transactions of Civil Engineering . 2019,第JulSuppla1期

机译：使用高斯过程回归测定吸盘隆起容量，Minimax概率机回归和极限学习机
3. On the uncertainty analysis of uplift capacity of suction caissons in clay based on the fuzzy sets theory [J] . Derakhshani Ali Ocean Engineering . 2018,第DECa15期

机译：基于模糊集理论的黏土沉箱提升能力不确定性分析
4. Vertical uplift capacity of suction caisson in clay [C] . L. Thorel, J. Garnier, G. Rault, International Symposium on Frontiers in Offshore Geotechnics . 2005

机译：在粘土中吸附的垂直隆起容量
5. Extension of the Regression Method for Imputation of Data with Monotone Missing Pattern using Multivariate Adaptive Regression Splines (MARS), with Applications to Systematic- Missing-At-Random (SMAR) Study Designs [D] . Lu, Feng. 2013

机译：利用多元自适应回归样条（MARS）扩展单调缺失模式数据插补的回归方法，并应用于系统随机缺失研究（SMAR）研究设计
6. Shuffling multivariate adaptive regression splines and adaptive neuro-fuzzy inference system as tools for QSAR study of SARS inhibitors [O] . M. Jalali-Heravi, M. Asadollahi-Baboli, A. Mani-Varnosfaderani -1

机译：改组多元自适应回归样条和自适应神经模糊推理系统作为SARS抑制剂QSAR研究的工具
7. A finite element analysis of the pullout capacity of suction caissons in clay [O] . Sgardeli Christina G. (Georgia-Chrysouli C.) 2009

机译：粘土中吸力沉箱拉拔能力的有限元分析

Uplift capacity of suction caisson in clay using multivariate adaptive regression spline

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