Landslide displacement prediction based on time series and long short-term memory networks-Reference-Cited by-同舟云学术

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Landslide displacement prediction based on time series and long short-term memory networks

Published:2024-06-07 Issue:7 Volume:83 Page:
ISSN:1435-9529
Container-title:Bulletin of Engineering Geology and the Environment
language:en
Short-container-title:Bull Eng Geol Environ

Author:

Jin Anjie,Yang Shasha,Huang Xuri

Funder

Science and Technology Personnel Service Enterprise Project of Xi ’an Science and Technology Bureau

Shaanxi Provincial Department of Education 2022 General Special Scientific Research Program Project

Yan’an University Doctoral Research Initiation Program

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10064-024-03714-w.pdf

Reference54 articles.

1. Abancó C, Bennett GL, Matthews AJ et al (2021) The role of geomorphology, rainfall and soil moisture in the occurrence of landslides triggered by 2018 typhoon mangkhut in the philippines. Nat Hazards Earth Syst Sci 21(5):1531–1550. https://doi.org/10.5194/nhess-21-1531-2021

2. Aggarwal A, Alshehri M, Kumar M et al (2020) Landslide data analysis using various time-series forecasting models. Comput Electr Eng 88:106858. https://doi.org/10.1016/j.compeleceng.2020.106858

3. Bengio Y, Simard P, Frasconi P (1994) Learning long-term dependencies with gradient descent is difficult. IEEE Trans Neural Netw 5(2):157–166. https://doi.org/10.1109/72.279181

4. Chen SY, Chou WY (2012) Short-term traffic flow prediction using emd-based recurrent hermite neural network approach. In: 2012 15th International IEEE Conference on intelligent transportation systems, pp 1821–1826, https://doi.org/10.1109/ITSC.2012.6338665

5. Deng L, Smith A, Dixon N et al (2021) Machine learning prediction of landslide deformation behaviour using acoustic emission and rainfall measurements. Eng Geol 293:106315. https://doi.org/10.1016/j.enggeo.2021.106315

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1. The forecasting of surface displacement for tunnel slopes utilizing the WD-IPSO-GRU model;Scientific Reports;2024-09-05

2. Landslide Assessment Classification Using Deep Neural Networks Based on Climate and Geospatial Data;Sustainability;2024-08-17

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