IMHE OpenIR  > Journal of Mountain Science  > Journal of Mountain Science-2017  > Vol14 No.9
A back-propagation neural-network-based displacement back analysis for the identification of the geomechanical parameters of the Yonglang landslide in China
Yu, Fang-wei1; Peng, Xiong-zhi2; Su, Li-jun1,3,4
2017
Source PublicationJOURNAL OF MOUNTAIN SCIENCE
ISSN1672-6316
EISSN1993-0321
Volume14Issue:9Pages:1739-1750
SubtypeArticle
AbstractXigeda 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.
KeywordBack-propagation Neural Network Displacement Back Analysis Geomechanical Parameters Landslide Numerical Analysis Uniform Design Xigeda Formation
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
DOI10.1007/s11629-016-4193-y
WOS Subject ExtendedEnvironmental Sciences & Ecology
Indexed BySCI
WOS KeywordMODELING AXIAL CAPACITY ; MARQUARDT ALGORITHM ; PILE FOUNDATIONS ; UNIFORM DESIGN ; ROCK ; SETTLEMENT ; EVOLUTION ; TUNNEL ; SITE
Language英语
Quartile4区
TOP
WOS SubjectEnvironmental Sciences
WOS IDWOS:000409490000006
Funding Organization"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)
PublisherSCIENCE PRESS
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/19071
CollectionJournal of Mountain Science_Journal of Mountain Science-2017_Vol14 No.9
山地灾害与地表过程重点实验室
Corresponding AuthorPeng, Xiong-zhi
Affiliation1.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
First Author Affilication中国科学院水利部成都山地灾害与环境研究所
Recommended Citation
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.
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