基于统计方法的边坡稳定性评价研究
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摘要
本文以福建漳龙高速公路漳州到龙岩段97处边坡做为研究对象,通过实地调查,选取影响边坡稳定性的9项因子,运用模糊综合评判法、RBF人工神经网络法和多元不安定指数分析法三种统计方法,分别建立边坡稳定性影响因子与破坏程度间的关系,确定各影响因子对边坡的影响程度,预测边坡破坏发生的可能性,同时,针对边坡稳定性系数1这一判别准则并不能反映不同工程对边坡不同稳定性的要求,细划了边坡稳定性分类,以稳定系数1.2做为判别准则。通过对三种方法分析结果的综合评判,认为RBF人工神经网络分析法是最佳的分析模式;影响边坡稳定最重要的诱发因子是降雨量,潜在因子是岩体结构;提出了新的边坡稳定性分类:稳定、潜在不稳定和不稳定。
In this paper, we choose 97 side slopes from Zhang Zhou to Long Yan high-speed road as the study of slope. Through on-the-spot investigation, selection influence side slope stable 9 factors, utilization fuzzy comprehensive judgment, RBF artificial nerve network method and multi-dimensional astatic index method of analysis three statistical methods, establishes the side slope stability influence factor and the destructiveness relations separately, determined that each influence factor to the side slope the influence, forecast the side slope destruction occurs the possibility, At the same time, the slope stability factor of 1 criteria do not reflect the different works on the stability of the requirements of different slope, so small slope damage classification designated to stabilize the coefficient of 1.2 as a criterion.Through three methods analysis result's synthesis judgment, we thought that the RBF artificial neural networks analytic method is the best analysis pattern; The influence stability of slope most important suggestion factor is a rainfall amount, the latent factor is the rock mass structure; Proposed the new side slope stability classification is stable, latent unstable and unstable.
In this paper, we choose 97 side slopes from Zhang Zhou to Long Yan high-speed road as the study of slope. Through on-the-spot investigation, selection influence side slope stable 9 factors, utilization fuzzy comprehensive judgment, RBF artificial nerve network method and multi-dimensional astatic index method of analysis three statistical methods, establishes the side slope stability influence factor and the destructiveness relations separately, determined that each influence factor to the side slope the influence, forecast the side slope destruction occurs the possibility, At the same time, the slope stability factor of 1 criteria do not reflect the different works on the stability of the requirements of different slope, so small slope damage classification designated to stabilize the coefficient of 1.2 as a criterion.Through three methods analysis result's synthesis judgment, we thought that the RBF artificial neural networks analytic method is the best analysis pattern; The influence stability of slope most important suggestion factor is a rainfall amount, the latent factor is the rock mass structure; Proposed the new side slope stability classification is stable, latent unstable and unstable.
引文
[1]孙广忠.地质工程理论与实践[D].北京:地震出版社,1988:35~38.
[2]张咸恭,王思敬,张倬元等.中国工程地质学[M].北京:科学出版社,2000:46~58.
[3]李智毅,杨裕云.工程地质学概论[D].北京:中国地质大学出版社,1996:21~30.
[4]李建华.岩坡稳定的层次模糊综合评价法[J].贵州工学院学报,1992,21(4):60~58.
[5]杨伦标,高英议.模糊数学原理及其应用[M].华南理工大学出版社,1993:70~78.
[6]陈祖煜.土质边坡稳定分析—原理·方法·程序[D].北京:中国水利水电出版社,2003:32~45.
[7] Gomez H. and Kavzoglu T. Assessment of shallow landslide susceptibility usingartificial neural networks[J].In Jabonosa River Basin,Venezuela, Engineering Geology,2004:32~40.
[8]邓聚龙.灰理论基础[M].武汉:华中科技大学出版社,2002:32~45.
[9]吴益平,唐辉明.滑坡灾害空间预测研究[J].地质科技情报,2001,20(2):87~90.
[10]简文彬,姚环,焦述强等.漳(州)--龙(岩)高速公路石崆山边坡稳定性评价[J].岩石力学与工程学报,2002,21(1):43~47.
[11]祝玉学.边坡可靠性分析[M].北京:冶金工业出版社,1993:46~58.
[12]秦四清.滑坡工程防治优化设计与信息化施工[J].中国地质灾害与防治学报,1999:46~58.
[13]李洪兴,蒋金泉等.工程模糊数学方法及其应用[M].天津科学技术出版社,1993,21(4):60~58.
[14]张跃,邹寿平,宿芬等.模糊数学方法及其应用[M].煤炭工业出版社,1992:21~30.
[15]贺仲雄.模糊数学及其运用[M].天津科学技术出版社,1983:101~130.
[16]湛红.模糊数学在国民经济中的应用[M].华中理工大学出版社,1994:87~110.
[17]王元汉,刘瑞伶.边坡稳定的Fuzzy综合评判法[J].华中理工大学学报,1998,5(l):96~98.
[18]谢华,朱学峰.模糊综合评判中几种数学模型的比较[J].广东自动化与信息工程,2001,22(4):5~7.
[19]夏元友,朱瑞赓.不稳定边坡治理方案的多层次模糊综合群决策[J].自然灾害学报,1998,3(1):60~65.
[20]王宏涛.模糊综合评判法在工程项目风险分析中的应用[D]:[硕士学位论文].深圳:深圳大学,2004,60~65.
[21]张晓晖,王辉,戴福初等.基于关系矩阵和模糊集合的斜坡稳定性综合评价[J].岩石力学与工程学报,2000,19(3):346~349.
[22]周继成等.人工神经网络[M].北京:科学普及出版社,1993:80~90.
[23]夏元友,李新平,朱瑞赓.基于人工神经网络的边坡稳定性工程地质评价方法[J].岩土力学,1996,6(3):27~33.
[24]飞思科技产品研发中心.神经网络理论与MATLAB7实现[M].北京:电子工业出版社, 2005:45~56.
[25]冯夏庭,王泳嘉,卢世宗.边坡稳定性的神经网络估计[J].工程地质学报,1995,3(4):54-61.
[26]张际先,余茂祚.神经网络及其在工程的应用[M].北京:机械工业出版社,1996:57~73.
[27]杨运林,盛建龙.基于人工神经网络的边坡安全系数估算[J].矿业研究与开发,2006,26(1):56-61.
[28]王洪元,史国栋.人工神经网络技术及其应用[M].北京:中国石化出版社, 2002:97~103.
[29]张友民,李庆国,戴冠中.一种RBF网络结构优化方法[J].控制与决策, 1996,11(6):67~71.
[30] XU X H, WANG Q Y.Emergence of Uncertainty Information and itsClassification[M].武汉:华中理工大学出版社,1994:35~60.
[31]徐林生,王兰生,李天斌.国内外岩爆研究现状综述[J].长江科学院院报,1999,12(6):65~69.
[32]陈时祖.台湾西南部地区泥页岩研究之工程地质特性[J].地工技术杂志,1994,9(5):30~34.
[33] Hillel Daniel, Fundamental of soil physics[J], John Willey & Sons Inc, 1982,15(3): 50~54.
[34] Das M B. Principles of Geotechnical Engineering[J]. Brooks / Cole Thomson Learning, 2002,10(3): 30~34.
[35] Shu-Yi Lin,C. T. Lee.Linkou Tableland with the Assistance of Principal Component Analysis.Institute of Applied Geology[J].National Central University , 1999,10(3): 30~34.
[2]张咸恭,王思敬,张倬元等.中国工程地质学[M].北京:科学出版社,2000:46~58.
[3]李智毅,杨裕云.工程地质学概论[D].北京:中国地质大学出版社,1996:21~30.
[4]李建华.岩坡稳定的层次模糊综合评价法[J].贵州工学院学报,1992,21(4):60~58.
[5]杨伦标,高英议.模糊数学原理及其应用[M].华南理工大学出版社,1993:70~78.
[6]陈祖煜.土质边坡稳定分析—原理·方法·程序[D].北京:中国水利水电出版社,2003:32~45.
[7] Gomez H. and Kavzoglu T. Assessment of shallow landslide susceptibility usingartificial neural networks[J].In Jabonosa River Basin,Venezuela, Engineering Geology,2004:32~40.
[8]邓聚龙.灰理论基础[M].武汉:华中科技大学出版社,2002:32~45.
[9]吴益平,唐辉明.滑坡灾害空间预测研究[J].地质科技情报,2001,20(2):87~90.
[10]简文彬,姚环,焦述强等.漳(州)--龙(岩)高速公路石崆山边坡稳定性评价[J].岩石力学与工程学报,2002,21(1):43~47.
[11]祝玉学.边坡可靠性分析[M].北京:冶金工业出版社,1993:46~58.
[12]秦四清.滑坡工程防治优化设计与信息化施工[J].中国地质灾害与防治学报,1999:46~58.
[13]李洪兴,蒋金泉等.工程模糊数学方法及其应用[M].天津科学技术出版社,1993,21(4):60~58.
[14]张跃,邹寿平,宿芬等.模糊数学方法及其应用[M].煤炭工业出版社,1992:21~30.
[15]贺仲雄.模糊数学及其运用[M].天津科学技术出版社,1983:101~130.
[16]湛红.模糊数学在国民经济中的应用[M].华中理工大学出版社,1994:87~110.
[17]王元汉,刘瑞伶.边坡稳定的Fuzzy综合评判法[J].华中理工大学学报,1998,5(l):96~98.
[18]谢华,朱学峰.模糊综合评判中几种数学模型的比较[J].广东自动化与信息工程,2001,22(4):5~7.
[19]夏元友,朱瑞赓.不稳定边坡治理方案的多层次模糊综合群决策[J].自然灾害学报,1998,3(1):60~65.
[20]王宏涛.模糊综合评判法在工程项目风险分析中的应用[D]:[硕士学位论文].深圳:深圳大学,2004,60~65.
[21]张晓晖,王辉,戴福初等.基于关系矩阵和模糊集合的斜坡稳定性综合评价[J].岩石力学与工程学报,2000,19(3):346~349.
[22]周继成等.人工神经网络[M].北京:科学普及出版社,1993:80~90.
[23]夏元友,李新平,朱瑞赓.基于人工神经网络的边坡稳定性工程地质评价方法[J].岩土力学,1996,6(3):27~33.
[24]飞思科技产品研发中心.神经网络理论与MATLAB7实现[M].北京:电子工业出版社, 2005:45~56.
[25]冯夏庭,王泳嘉,卢世宗.边坡稳定性的神经网络估计[J].工程地质学报,1995,3(4):54-61.
[26]张际先,余茂祚.神经网络及其在工程的应用[M].北京:机械工业出版社,1996:57~73.
[27]杨运林,盛建龙.基于人工神经网络的边坡安全系数估算[J].矿业研究与开发,2006,26(1):56-61.
[28]王洪元,史国栋.人工神经网络技术及其应用[M].北京:中国石化出版社, 2002:97~103.
[29]张友民,李庆国,戴冠中.一种RBF网络结构优化方法[J].控制与决策, 1996,11(6):67~71.
[30] XU X H, WANG Q Y.Emergence of Uncertainty Information and itsClassification[M].武汉:华中理工大学出版社,1994:35~60.
[31]徐林生,王兰生,李天斌.国内外岩爆研究现状综述[J].长江科学院院报,1999,12(6):65~69.
[32]陈时祖.台湾西南部地区泥页岩研究之工程地质特性[J].地工技术杂志,1994,9(5):30~34.
[33] Hillel Daniel, Fundamental of soil physics[J], John Willey & Sons Inc, 1982,15(3): 50~54.
[34] Das M B. Principles of Geotechnical Engineering[J]. Brooks / Cole Thomson Learning, 2002,10(3): 30~34.
[35] Shu-Yi Lin,C. T. Lee.Linkou Tableland with the Assistance of Principal Component Analysis.Institute of Applied Geology[J].National Central University , 1999,10(3): 30~34.