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A back-propagation neural-network-based displacement back analysis for the identification of the geomechanical parameters of the Yonglang landslide in China 被引量:1
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作者 YU Fang-wei PENG Xiong-zhi SU Li-jun 《Journal of Mountain Science》 SCIE CSCD 2017年第9期1739-1750,共12页
Xigeda formation is a type of hundredmeter-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... Xigeda formation is a type of hundredmeter-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(FLAC3D) to acquire a database of the geomechanical parameters of the Yonglang landslide and the corresponding displacements of the loadingtest 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 neuralnetwork-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. 展开更多
关键词 Back-propagation neural network Displacement back analysis Geomechanical parameters Landslide Numerical analysis Uniform design Xigeda formation
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Erratum to "Uniform Coverage of Fibres over Open-contoured Freeform Structure Based on Arc-length Parameter" [Chinese Journal of Aeronautics 21(2008)571-577] 被引量:2
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作者 Wang Xiaoping An Luling +1 位作者 Zhang Liyan Zhou Laishui 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2009年第3期256-256,共1页
It is regretted that the author corrections requested at the proof stage were not made accurately. There are some incorrect typings in two equations which will lead to inaccurate results if readers perform calculation... It is regretted that the author corrections requested at the proof stage were not made accurately. There are some incorrect typings in two equations which will lead to inaccurate results if readers perform calculations directly 展开更多
关键词 length OVER Chinese Journal of Aeronautics 21 Erratum to Uniform Coverage of Fibres over Open-contoured Freeform Structure Based on Arc-length parameter Open Arc
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A PARAMETER-UNIFORM TAILORED FINITE POINT METHOD FOR SINGULARLY PERTURBED LINEAR ODE SYSTEMS*
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作者 Houde Han J.J.H. Miller Min Tang 《Journal of Computational Mathematics》 SCIE CSCD 2013年第4期422-438,共17页
In scientific applications from plasma to chemical kinetics, a wide range of temporal scales can present in a system of differential equations. A major difficulty is encountered due to the stiffness of the system and ... In scientific applications from plasma to chemical kinetics, a wide range of temporal scales can present in a system of differential equations. A major difficulty is encountered due to the stiffness of the system and it is required to develop fast numerical schemes that are able to access previously unattainable parameter regimes. In this work, we consider an initial-final value problem for a multi-scale singularly perturbed system of linear ordi- nary differential equations with discontinuous coefficients. We construct a tailored finite point method, which yields approximate solutions that converge in the maximum norm, uniformly with respect to the singular perturbation parameters, to the exact solution. A parameter-uniform error estimate in the maximum norm is also proved. The results of numerical experiments, that support the theoretical results, are reported. 展开更多
关键词 Tailored finite point method parameter uniform Singular perturbation ODEsystem.
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