基于BP神经网络的第四系覆盖物厚度预测及三维地质建模

张瀚; 桂蕾; 王腾飞; 杨赛

doi:10.3799/dqkx.2022.173

Volume 49 Issue 2

Feb. 2024

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Article Navigation > Earth Science > 2024 > 49(2): 550-559

Zhang Han, Gui Lei, Wang Tengfei, Yang Sai, 2024. Prediction of Quaternary Cover Thickness and 3D Geological Modeling Based on BP Neural Network. Earth Science, 49(2): 550-559. doi: 10.3799/dqkx.2022.173

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Zhang Han, Gui Lei, Wang Tengfei, Yang Sai, 2024. Prediction of Quaternary Cover Thickness and 3D Geological Modeling Based on BP Neural Network. Earth Science, 49(2): 550-559. doi: 10.3799/dqkx.2022.173

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Prediction of Quaternary Cover Thickness and 3D Geological Modeling Based on BP Neural Network

doi: 10.3799/dqkx.2022.173

Zhang Han^{1
,
,},
Gui Lei^{1
,
,
,},
Wang Tengfei¹,
Yang Sai²

1.
Faculty of Engineering, China University of Geosciences, Wuhan 430074, China
2.
Geological Survey and Research Institute, China University of Geosciences, Wuhan 430074, China

Received Date: 2022-11-12
Publish Date: 2024-02-25

Abstract

Abstract

Fine investigation and assessment of geological disaster risk is an important part of prevention and control of geological disaster reduction at present. The development of 3D slope geological modeling technology provides a new idea for detailed investigation and assessment of landslide hazard risk, which can greatly improve the efficiency and assessment accuracy of landslide hazard investigation in the region.In this paper, based on Skua-Gocad platform, three-dimensional geological modeling technology of regional slope is studied for two modules of Quaternary cover and underlying bedrock. Taking Dazhou Town, Wanzhou District, Chongqing as an example, BP neural network model is used to predict the thickness of Quaternary cover by building a multi-dimensional nonlinear network of Quaternary cover thickness and geological environment indicators in the study area.Combined with the field survey data, the method is verified, and the prediction accuracy of Quaternary cover thickness based on BP neural network reaches 91.49%. On this basis, a 3D geological model is built, which has good visualization effect and ensures the reliability of data.It overcomes the shortcoming of traditional Kriging interpolation method that can't reflect geological environment factors, and solves the difficult problem of prediction of Quaternary cover thickness in regional scope.
- quaternary covering,
- forecast,
- BP neural network,
- three-dimensional geological construction,
- engineering geology

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References(47)

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Prediction of Quaternary Cover Thickness and 3D Geological Modeling Based on BP Neural Network

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