A STUDY OF SLOPE STABILITY PREDICTION USING LEAST SQUARE SUPPORT VECTOR MACHINE

P. SAMUI

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A STUDY OF SLOPE STABILITY PREDICTION USING LEAST SQUARE SUPPORT VECTOR MACHINE

机译：最小二乘支持向量机预测边坡稳定性的研究。

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The determination of stability of slope is an important task in geological engineering practice. This paper proposes the use of the least square support vector machine (LSSVM) for the determination of stability of slope. The LSSVM is a statistical learning method which has a self-contained basis of statistical-learning theory and excellent learning performance. The five input variables used for the LSSVM model in this study are the unit weight (d), cohesion (c), angle of internal friction (φ), slope angle (β), height (H) and pore water pressure coefficient (r_u). The LSVM model also gives a probabilistic output. This study shows that the LSSVM model is a robust tool for slope stability analysis.

机译：确定边坡的稳定性是地质工程实践中的重要任务。本文提出使用最小二乘支持向量机（LSSVM）确定边坡的稳定性。 LSSVM是一种统计学习方法，它具有独立的统计学习理论基础和出色的学习性能。本研究中用于LSSVM模型的五个输入变量是单位重量（d），内聚力（c），内摩擦角（φ），倾斜角（β），高度（H）和孔隙水压力系数（r_u））。 LSVM模型还给出了概率输出。这项研究表明，LSSVM模型是边坡稳定性分析的可靠工具。

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来源
《Applied Mechanics and Engineering》 |2012年第1期|p.279-287|共9页
作者
P. SAMUI;
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作者单位

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

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原文格式 PDF
正文语种 eng
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关键词
slope stability; least square support vector machine; prediction; statistical learning algorithm;

机译：边坡稳定性最小二乘支持向量机预测;统计学习算法;

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专利

1. A STUDY OF SLOPE STABILITY PREDICTION USING LEAST SQUARE SUPPORT VECTOR MACHINE [J] . P. SAMUI International Journal of Applied Mechanics and Engineering . 2012,第1期

机译：最小二乘支持向量机在边坡稳定性预测中的应用研究。
2. Slope stability analysis based on quantum-behaved particle swarm optimization and least squares support vector machine [J] . Bo Li, Duanyou Li, Zhijun Zhang, Applied Mathematical Modelling . 2015,第17期

机译：基于量子行为粒子群优化和最小二乘支持向量机的边坡稳定性分析
3. Prediction of water quality index (WQI) using support vector machine (SVM) and least square-support vector machine (LS-SVM) [J] . Wei Cong Leong, Alireza Bahadori, Jie Zhang, International journal of river basin management . 2021,第2期

机译：使用支持向量机（SVM）和最小二乘支持向量机（LS-SVM）预测水质指数（WQI）
4. A Comparative Study of Slope Failure Prediction Using Logistic Regression, Support Vector Machine and Least Square Support Vector Machine Models [C] . Lim Yi Zhou, Fam Pei Shan, Kunio Shimizu, National Symposium on Mathematical Sciences . 2017

机译：逻辑回归坡度故障预测的比较研究，支持向量机和最小二乘支持向量机模型
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6. Study of ARIMA and least square support vector machine (LS-SVM) models for the prediction of SARS-CoV-2 confirmed cases in the most affected countries [O] . Sarbjit Singh, Kulwinder Singh Parmar, Sidhu Jitendra Singh Makkhan, -1

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7. Utilization of a least square support vector machine (LSSVM) for slope stability analysis [O] . Samui P., Kothari D.P. 2011

机译：利用最小二乘支持向量机（LSSVM）进行边坡稳定性分析

A STUDY OF SLOPE STABILITY PREDICTION USING LEAST SQUARE SUPPORT VECTOR MACHINE

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