A back-propagation neural-network-based displacement back analysis for the identification of the geomechanical parameters of the Yonglang landslide in China
文献类型：期刊论文
| 作者 | Yu, Fang-wei1 ; Peng, Xiong-zhi2; Su, Li-jun1,3,4
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| 刊名 | JOURNAL OF MOUNTAIN SCIENCE
 |
| 出版日期 | 2017-09-01 |
| 卷号 | 14期号:9页码:1739-1750 |
| ISSN号 | 1672-6316 |
| 关键词 | Back-propagation Neural Network Displacement Back Analysis Geomechanical Parameters Landslide Numerical Analysis Uniform Design Xigeda Formation |
| DOI | 10.1007/s11629-016-4193-y |
| 文献子类 | Article |
| 英文摘要 | Xigeda formation is a type of hundred-meter-thick lacustrine sediments of being prone to triggering landslides along the trunk channel and tributaries of the upper Yangtze River in China. The Yonglang landslide located near Yonglang Town of Dechang County in Sichuan Province of China, which was a typical Xigeda formation landslide, was stabilized by anti-slide piles. Loading tests on a loading-test pile were conducted to measure the displacements and moments. The uncertainty of the tested geomechanical parameters of the Yonglang landslide over certain ranges would be problematic during the evaluation of the landslide. Thus, uniform design was introduced in the experimental design, and by which, numerical analyses of the loading-test pile were performed using Fast Lagrangian Analysis of Continua (FLAC(3D)) to acquire a database of the geomechanical parameters of the Yonglang landslide and the corresponding displacements of the loading-test pile. A three-layer back-propagation neural network was established and trained with the database, and then tested and verified for its accuracy and reliability in numerical simulations. Displacement back analysis was conducted by substituting the displacements of the loading-test pile to the well-trained three-layer back-propagation neural network so as to identify the geomechanical parameters of the Yonglang landslide. The neural-network-based displacement back analysis method with the proposed methodology is verified to be accurate and reliable for the identification of the uncertain geomechanical parameters of landslides. |
| WOS关键词 | MODELING AXIAL CAPACITY ; MARQUARDT ALGORITHM ; PILE FOUNDATIONS ; UNIFORM DESIGN ; ROCK ; SETTLEMENT ; EVOLUTION ; TUNNEL ; SITE |
| 语种 | 英语 |
| 出版者 | SCIENCE PRESS |
| WOS记录号 | WOS:000409490000006 |
| 资助机构 | "Light of West China" Program of Chinese Academy of Sciences(Y6R2250250) ; National Basic Research Program of China (973 Program)(2013CB733201) ; One-Hundred Talents Program of Chinese Academy of Sciences ; Key Research Program of Frontier Sciences, Chinese Academy of Sciences(QYZDB-SSW-DQC010) ; Youth Fund of Institute of Mountain Hazards and Environment, Chinese Academy of Sciences(Y6K2110110) |
| 源URL | [http://ir.imde.ac.cn/handle/131551/19071]  |
| 专题 | Journal of Mountain Science _Journal of Mountain Science-2017_Vol14 No.9 成都山地灾害与环境研究所_山地灾害与地表过程重点实验室 |
| 通讯作者 | Peng, Xiong-zhi |
| 作者单位 | 1.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Sichuan, Peoples R China 2.Southwest Jiaotong Univ, Dept Civil Engn, Chengdu 610031, Sichuan, Peoples R China 3.CAS Ctr Excellence Tibetan Plateau Earth Sci, Beijing 100101, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yu, Fang-wei,Peng, Xiong-zhi,Su, Li-jun. A back-propagation neural-network-based displacement back analysis for the identification of the geomechanical parameters of the Yonglang landslide in China[J]. JOURNAL OF MOUNTAIN SCIENCE,2017,14(9):1739-1750. |
| APA | Yu, Fang-wei,Peng, Xiong-zhi,&Su, Li-jun.(2017).A back-propagation neural-network-based displacement back analysis for the identification of the geomechanical parameters of the Yonglang landslide in China.JOURNAL OF MOUNTAIN SCIENCE,14(9),1739-1750. |
| MLA | Yu, Fang-wei,et al."A back-propagation neural-network-based displacement back analysis for the identification of the geomechanical parameters of the Yonglang landslide in China".JOURNAL OF MOUNTAIN SCIENCE 14.9(2017):1739-1750. |
入库方式： OAI收割
来源：成都山地灾害与环境研究所
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