Physics-informed optimization for a data-driven approach in landslide susceptibility evaluation

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外文摘要：Landslide susceptibility mapping is an integral part of geological hazard analysis.Recently,the emphasis of many studies has been on data-driven models,notably those derived from machine learning,owing to their aptitude for tackling complex non-linear problems.However,the prevailing models often disregard qualitative research,leading to limited interpretability and mistakes in extracting negative samples,i.e.inaccurate non-landslide samples.In this study,Scoops 3D(a three-dimensional slope stability analysis tool)was utilized to conduct a qualitative assessment of slope stability in the Yunyang section of the Three Gorges Reservoir area.The depth of the bedrock was predicted utilizing a Convolutional Neural Network(CNN),incorporating local boreholes and building on the insights from prior research.The Random Forest(RF)algorithm was subsequently used to execute a data-driven landslide susceptibility analysis.The proposed methodology demonstrated a notable increase of 29.25％in the evaluation metric,the area under the receiver operating characteristic curve(ROC-AUC),outperforming the prevailing benchmark model.Furthermore,the landslide susceptibility map generated by the proposed model demonstrated superior interpretability.This result not only validates the effectiveness of amalgamating mathematical and mechanistic insights for such analyses,but it also carries substantial academic and practical implications.

外文关键词：

Physics-informedMachine learningBedrock depthScoops 3DLandslide susceptibility

作者：

Songlin Liu、Luqi Wang、Wengang Zhang、Weixin Sun、Yunhao Wang、Jianping Liu

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作者单位：

School of Civil Engineering,Chongqing University,Chongqing,400045,China

Key Laboratory of New Technology for Construction of Cities in Mountain Area,Chongqing University,Ministry of Education,Chongqing,400045,China

National Joint Engineering Research Center of Geohazards Prevention in the Reservoir Areas,Chongqing University,Chongqing,400045,China

Chongqing Field Scientific Observation Station for Landslide Hazards in Three Gorges Reservoir Area,Chongqing University,Chongqing,400045,China

Chongqing Mingfeng Construction Engineering Co.,Ltd,Chongqing,405800,China

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基金：

Sichuan Transportation Science and Technology ProjectHighend Foreign Expert Introduction programScience and Technology Research Program of Chongqing Municipal Education Commission

项目编号：

2018-ZL-01G2022165004LHZ2021001

出版年：

2024

DOI：

10.1016/j.jrmge.2023.11.039

岩石力学与岩土工程学报(英文版)

中国科学院武汉岩土力学所中国岩石力学与工程学会武汉大学

岩石力学与岩土工程学报(英文版)

CSTPCD

影响因子：0.404

ISSN：1674-7755

年,卷(期)：2024.16(8)