|本期目录/Table of Contents|

[1]陈祖云,张桂珍,邬长福,等.基于支持向量机的边坡稳定性预测研究 *[J].中国安全生产科学技术,2009,5(4):101-105.
 CHEN Zu yun,ZHANG Gui zhen,WU Chang fu,et al.Study of prediction of slope stability based on support vector machines[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2009,5(4):101-105.
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基于支持向量机的边坡稳定性预测研究 *()
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
5
期数:
2009年4
页码:
101-105
栏目:
出版日期:
2009-08-31

文章信息/Info

Title:
Study of prediction of slope stability based on support vector machines
文章编号:
1673-193X(2009)-04-0101-05
作者:
陈祖云 1张桂珍 1邬长福 1杨胜强 2
1.江西理工大学资源与环境工程学院2.中国矿业大学安全工程学院
Author(s):
CHEN Zuyun1 ZHANG Guizhen1 WU Changfu1 YANG Shengqiang2
1.Faculty of Environmental and Architectural Engineering, Jiangxi University of Science and Technology2.Faculty of Safety Science Engineering, China University of Mining and Technology
关键词:
边坡稳定性支持向量机预测
Keywords:
slope stability support vector machines prediction
分类号:
X936
DOI:
-
文献标志码:
A
摘要:
针对边坡稳定性影响因素复杂,传统的稳定性分析存在计算量大、计算过程复杂的问题,提出了边坡稳定性的支持向量机预测方法。分析了边坡稳定性的影响因素,选择影响边坡稳定性的边坡重度、内聚力、摩擦角、边坡角、边坡高度、孔隙压力比6项指标为特征向量。并运行该方法对典型边坡实例进行了预测,预测结果与边坡稳定性实际状态及其它方法预测结果相吻合,表明了支持向量机在边坡稳定性预测中的可靠性和有效性。
Abstract:
The method of support vector machines was applied in the prediction of the slope stability in order to solve the problems such as the complexity of slope stability factors and the hugeness of computation workload by the traditional slope stability analysis method. The impact factors of slope stability were analysised, then six indicators,which include slope gravity,cohesion force,friction angle,slope angle,slope height and pore pressure ratio,were used in slope stability analysis and choosed as characteristic vector. Typical project examples were forecasted in the aspect of slope stability by support vector machines. The slope stability prediction results by SVM coincided with not only the actual status, but also the results by other methods of prediction. It showed that support vector machine prediction of slope stability are reliability and effectiveness.

参考文献/References:

[1] 刘玉静.基于进化神经网络的岩土边坡稳定性预测方法[J]. 煤矿安全, 2005,36(8):48~50.LIU Yujing. A Method for the stability Prediction of the Rocksoil Slope based on Evolution Nerve Network[J].Safety in Coal Mines, 2005,36(8):48~50 [2] 熊建秋,李祚泳. 用概率神经网络对水电边坡稳定性预测[J]. 路基工程, 2006,127(4):12~15.XIONG Jianqiu, LI Zuoyong. The stability Prediction of the Water Electricity Slope based on Probability Nerve Network[J].Subgrade Engineering, 2006,127(4):12~15 [3] Ilias Maglogiannis, Elias Zafiropoulos, Ioannis Anagnostopoulos. An intelligent system for automated breast cancer diagnosis and prognosis using SVM based classifiers[J]. Applied Intelligence,2007(7):24~36 [4] 姜德义,朱合华,杜云贵.边坡稳定性分析与滑坡防治[M].重庆:重庆大学出版,2005 [5] 李克庆,谢玉铃,徐九华.基于两类总体的边坡稳定性判别分析[J].北京科技大学学报,2008, 30(4):344~348.LI Keqing,XIE Yuling,XU Jiuhua.Discriminant analysis of slope stability for two populations[J].JournalofUniversityofScienceandTechnologyBeijing, 2008, 30(4):344~348

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备注/Memo

备注/Memo:
收稿日期:2009-06-12作者简介:陈祖云(1972-),男,博士,副教授。*基金项目:江西省教育厅资助项目:GJJ09240、赣教技字[2007]212号。
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