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A platform for research: civil engineering, architecture and urbanism
Displacement Prediction of Jiuxianping Landslide Using GRU Networks
Displacement prediction plays a significant role in the landslide disaster early warning. However, landslide deformation is a complex nonlinear dynamic process, posing difficulties in the displacement prediction especially for the commonly used static models. This chapter applies an advanced deep machine learning method called gated recurrent unit (GRU) to the displacement prediction of the Jiuxianping landslide, which is a typical reservoir landslide located in the Yunyang County of Chongqing, China. Results show that the GRU-based approach is able to portray the variation of the periodic displacement in the testing dataset with fewer outliers. Different from the three static models, the GRU model is essentially a dynamic model making full use of the historical information, which can portray the deformation characteristics of the Jiuxianping landslide rationally.
Displacement Prediction of Jiuxianping Landslide Using GRU Networks
Displacement prediction plays a significant role in the landslide disaster early warning. However, landslide deformation is a complex nonlinear dynamic process, posing difficulties in the displacement prediction especially for the commonly used static models. This chapter applies an advanced deep machine learning method called gated recurrent unit (GRU) to the displacement prediction of the Jiuxianping landslide, which is a typical reservoir landslide located in the Yunyang County of Chongqing, China. Results show that the GRU-based approach is able to portray the variation of the periodic displacement in the testing dataset with fewer outliers. Different from the three static models, the GRU model is essentially a dynamic model making full use of the historical information, which can portray the deformation characteristics of the Jiuxianping landslide rationally.
Displacement Prediction of Jiuxianping Landslide Using GRU Networks
Wengang, Zhang (author) / Hanlong, Liu (author) / Lin, Wang (author) / Xing, Zhu (author) / Yanmei, Zhang (author)
Application of Machine Learning in Slope Stability Assessment ; Chapter: 7 ; 99-122
2023-07-09
24 pages
Article/Chapter (Book)
Electronic Resource
English
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