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

Journal of Rock Mechanics and Geotechnical Engineering 2024年第8期16卷 3192-3205页

作者： Songlin Liu luqi wang Wengang Zhang Weixin Sun Yunhao wang Jianping Liu School of Civil Engineering Chongqing UniversityChongqing400045China Key Laboratory of New Technology for Construction of Cities in Mountain Area Chongqing UniversityMinistry of EducationChongqing400045China National Joint Engineering Research Center of Geohazards Prevention in the Reservoir Areas Chongqing UniversityChongqing400045China Chongqing Field Scientific Observation Station for Landslide Hazards in Three Gorges Reservoir Area Chongqing UniversityChongqing400045China Chongqing Mingfeng Construction Engineering Co. LtdChongqing405800China

Landslide susceptibility mapping is an integral part of geological hazard ***,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 ***,the prevailing models often disregard qualitative research,leading to limited interpretability and mistakes in extracting negative samples,*** non-landslide *** 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 *** depth of the bedrock was predicted utilizing a Convolutional Neural Network(CNN),incorporating local boreholes and building on the insights from prior *** Random Forest(RF)algorithm was subsequently used to execute a data-driven landslide susceptibility *** 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 ***,the landslide susceptibility map generated by the proposed model demonstrated superior *** result not only validates the effectiveness of amalgamating mathematical and mechanistic insights for such analyses,but it also carries substantial academic and practical implications.

关键词： Physics-informed Machine learning Bedrock depth Scoops 3D Landslide susceptibility

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Time series prediction of reservoir bank landslide failure probability considering the spatial variability of soil properties

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第10期16卷 3951-3960页

作者： luqi wang Lin wang Wengang Zhang Xuanyu Meng Songlin Liu Chun Zhu School of Civil Engineering Chongqing UniversityChongqing400045China Key Laboratory of New Technology for Construction of Cities in Mountain Area Chongqing UniversityChongqing400045China National Joint Engineering Research Center of Geohazards Prevention in the Reservoir Areas Chongqing UniversityChongqing400045China School of National Safety and Emergency Management Beijing Normal UniversityZhuhai519087China School of Earth Sciences and Engineering Hohai UniversityNanjing210098China

Historically,landslides have been the primary type of geological disaster ***,the stability of reservoir banks is primarily affected by rainfall and reservoir water level ***,the stability of reservoir banks changes with the long-term dynamics of external disastercausing ***,assessing the time-varying reliability of reservoir landslides remains a *** this paper,a machine learning(ML)based approach is proposed to analyze the long-term reliability of reservoir bank landslides in spatially variable soils through time series *** study systematically investigated the prediction performances of three ML algorithms,*** perceptron(MLP),convolutional neural network(CNN),and long short-term memory(LSTM).Additionally,the effects of the data quantity and data ratio on the predictive power of deep learning models are *** results show that all three ML models can accurately depict the changes in the time-varying failure probability of reservoir *** CNN model outperforms both the MLP and LSTM models in predicting the failure ***,selecting the right data ratio can improve the prediction accuracy of the failure probability obtained by ML models.

关键词： Machine learning(ML) Reservoir bank landslide Spatial variability Time series prediction Failure probability

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Centrifuge modeling of unreinforced and multi-row stabilizing piles reinforced landslides subjected to reservoir water level fluctuation

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第5期16卷 1600-1614页

作者： Chenyang Zhang Yueping Yin Hui Yan Sainan Zhu Ming Zhang luqi wang Department of Civil Engineering The University of Hong KongHong KongChina China Institute of Geo-environment Monitoring BeijingChina Chongqing 107 Municipal Construction Engineering Co. Ltd.ChongqingChina Faculty of Engineering China University of GeosciencesWuhanChina School of Civil Engineering Chongqing UniversityChongqingChina

With the construction of the Three Gorges Reservoir dam,frequent reservoir landslide events have been *** recent years,multi-row stabilizing piles(MRSPs)have been used to stabilize massive reservoir landslides in *** this study,two centrifuge model tests were carried out to study the unreinforced and MRSP-reinforced slopes subjected to reservoir water level(RWL)operation,using the Taping landslide as a *** results indicate that the RWL rising can provide lateral support within the submerged zone and then produce the inward seepage force,eventually strengthening the slope ***,a rapid RWL drawdown may induce outward seepage forces and a sudden debuttressing effect,consequently reducing the effective soil normal stress and triggering partial pre-failure within the RWL fluctuation ***,partial deformation and subsequent soil structure damage generate excess pore water pressures,ultimately leading to the overall failure of the reservoir *** study also reveals that a rapid increase in the downslope driving force due to RWL drawdown significantly intensifies the lateral earth pressures exerted on the ***,the MRSPs possess a considerable reinforcement effect on the reservoir landslide,transforming the overall failure into a partial deformation and failure situated above and in front of the *** mechanical transfer behavior observed in the MRSPs demonstrates a progressive alteration in relation to RWL *** the RWL rises,the mechanical states among MRSPs exhibit a growing *** shear force transfer factor(*** ratio of shear forces on pile of the n th row to that of the first row)increases significantly with the RWL *** indicates that the mechanical states among MRSPs tend toward an enhanced *** insights gained from this study contribute to a more comprehensive understanding of the failure mechanisms of reservoir landslides and the mechanical behavior of M

关键词： Reservoir landslide Failure mechanism Multi-row stabilizing piles Mechanical behavior

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Inventory Policy for a Deteriorating Item with Time-Varying Demand Under Trade Credit and Inflation

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Journal of Systems Science and Information 2019年第2期10卷 115-133页

作者： luqi wang Zhijian CHEN Mingyao CHEN Ruijie ZHANG South China University of Technology Guangzhou 510640China China Tower Co. Harbin 151000China

It’s often the case that the supplier will provide the retailer with a permissible delay period in payments, during which the supplier charges the retailer no interest and the retailer accumulates interest earned from investment return. As a type of price reduction and an alternative to price discount,trade credit helps the supplier encourage the retailer’s ordering. This paper develops an inventory replenishment model for a deteriorating item with time-varying demand and shortages, taking account of trade credit and time value of money under inflation over a finite time horizon. This model is an extension and development of the existing studies related to the inventory system considering trade credit and time value of money and offers a more general model with more flexibility and resilience to handle the situation where demand of the end market is non-decreasing with regard to time.

关键词： inventory deteriorating items time-varying demand trade credit inflation

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Machine learning solution for regional landslide susceptibility based on fault zone division strategy

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Journal of Mountain Science 2024年第5期21卷 1745-1760页

作者： wang Yunhao wang luqi LIU Songlin SUN Weixin LIU Pengfei ZHU Lin YANG Wenyu GUO Tong School of Civil Engineering Chongqing UniversityChongqing 400045China Key Laboratory of New Technology for Construction of Cities in Mountain Area Chongqing UniversityMinistry of EducationChongqing 400045China National Joint Engineering Research Center of Geohazards Prevention in the Reservoir Areas Chongqing UniversityChongqing 400045China Institute of Geological Environment Monitoring Chongqing 401147China Chongqing 205 Geological Team Chongqing 401121China

Landslide susceptibility assessment is an essential tool for disaster prevention and management. In areas with multiple fault zones, the impact of fault zone on slope stability cannot be disregarded. This study performed qualitative analysis of fault zones and proposed a zoning method to assess the landslide susceptibility in Chengkou County, Chongqing Municipality, China. The region within a distance of 1 km from the faults was designated as sub-zone A, while the remaining area was labeled as sub-zone B. To accomplish the assessment, a dataset comprising 388 historical landslides and 388 non-landslide points was used to train the random forest model. 10-fold cross-validation was utilized to select the training and testing datasets for the model. The results of the models were analyzed and discussed, with a focus on model performance and prediction uncertainty. By implementing the proposed division strategy based on fault zone, the accuracy, precision, recall, F-score, and AUC of both two sub-zones surpassed those of the whole region. In comparison to the results obtained for the whole region, sub-zone B exhibited an increase in AUC by 6.15%, while sub-zone A demonstrated a corresponding increase of 1.66%. Moreover, the results of 100 random realizations indicated that the division strategy has little effect on the prediction uncertainty. This study introduces a novel approach to enhance the prediction accuracy of the landslide susceptibility mapping model in areas with multiple fault zones.

关键词： Landslide susceptibility mapping Fault division strategy Random forest GIS

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A physics-informed data-driven model for landslide susceptibility assessment in the Three Gorges Reservoir area

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Geoscience Frontiers 2023年第5期14卷 1-16页

作者： Songlin Liu luqi wang Wengang Zhang Weixin Sun Jie Fu Ting Xiao Zhenwei Dai School of Civil Engineering Chongqing UniversityChongqing 400045China Key Laboratory of New Technology for Construction of Cities in Mountain Area Chongqing UniversityMinistry of EducationChongqing 400045China National Joint Engineering Research Center of Geohazards Prevention in the Reservoir Areas Chongqing UniversityChongqing 400045China Chongqing Field Scientific Observation Station for Landslide Hazards in Three Gorges Reservoir Area Chongqing UniversityChongqing 400045China Center for Hydrogeology and Environmental Geology CGSBaoding Hebei 071051China Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring Ministry of EducationSchool of Geosciences and Info-PhysicsCentral South UniversityChangsha 410083China Central South China Innovation Center for Geosciences Wuhan Centre of China Geological SurveyWuhan 430205China

Landslide susceptibility mapping is a crucial tool for analyzing geohazards in a *** publications have popularized data-driven models,particularly machine learning-based methods,owing to their strong capability in dealing with complex nonlinear ***,a significant proportion of these models have neglected qualitative aspects during analysis,resulting in a lack of interpretability throughout the process and causing inaccuracies in the negative sample *** this study,Scoops 3D was employed as a physics-informed tool to qualitatively assess slope stability in the study area(the Hubei Province section of the Three Gorges Reservoir Area).The non-landslide samples were extracted based on the calculated factor of safety(FS).Subsequently,the random forest algorithm was employed for data-driven landslide susceptibility analysis,with the area under the receiver operating characteristic curve(AUC)serving as the model evaluation *** to the benchmark model(i.e.,the standard method of utilizing the pure random forest algorithm),the proposed method’s AUC value improved by 20.1%,validating the effectiveness of the dual-driven method(physics-informed data-driven).

关键词： Machine Learning Physics-informed Negative sample extraction Interpretability Dual-driven

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Amorphous porous sulfides nanosheets with hydrophilic/aerophobic surface for high-current-density water splitting

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Chinese Chemical Letters 2023年第7期34卷 230-235页

作者： Xiaoli Wu Sheng Zhao Lijie Yin luqi wang Linlin Li Feng Hu Shengjie Peng Jiangsu Key Laboratory of Electrochemical Energy Storage Technologies College of Materials Science and TechnologyNanjing University of Aeronautics and AstronauticsNanjing 210016China

The rational construction of electrocatalysts with desired features is significant but challenging for superior water splitting at high current density. Herein, amorphous Co Ni S nanosheets are synthesized on nickel foam(NF) through a facile structure evolution strategy and present advanced performance at high current densities in water splitting. The high catalytic activity can be attributed to the sufficient active sites exposed by the flexible amorphous configuration. Moreover, the hydrophilicity and aerophobicity of a-CoNiS/NF promote surface wettability of the self-supporting electrode and avoid the aggregation of bubbles, which expedites the diffusion of electrolyte and facilitates the mass transfer. As a result, the optimized electrode demonstrates low overpotentials of 289 and 434 m V at 500 m A/cm^(2) under alkaline conditions for hydrogen evolution reaction(HER) and oxygen evolution reaction(OER), respectively. Impressively, an electrolytic water splitting cell assembled by bifunctional a-Co Ni S/NF operates with a low cell voltage of 1.46 V@10 mA/cm^(2) and reaches 1.79 V at 500 mA/cm^(2). The strategy sheds light on a competitive platform for the reasonable design of non-precious-metal electrocatalysts under high current density.

关键词： Electrocatalysts Metal-organic frameworks Amorphous High current density Overall water splitting

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密近双星的质量比分布

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天文学进展 2024年第4期42卷 628-638页

作者：王禄齐刘超中国科学院大学北京100049 中国科学院国家天文台北京100101

双星演化是恒星物理的一个重要课题,它不仅对恒星研究,也对星系演化、超新星和宇宙学等研究有重要影响。LAMOST时域巡天提供了大量的双星样本,这对研究密近双星的统计性质非常重要。该文选择一批具有LAMOST时域光谱观测的主序短周期双星... 详细信息

双星演化是恒星物理的一个重要课题,它不仅对恒星研究,也对星系演化、超新星和宇宙学等研究有重要影响。LAMOST时域巡天提供了大量的双星样本,这对研究密近双星的统计性质非常重要。该文选择一批具有LAMOST时域光谱观测的主序短周期双星(主星质量在0.7M_(⊙)~2.2M_(⊙)之间)作为研究对象,通过the Joker获得了部分样本的双星轨道参数,并经由质量选择效应改正获得了这些密近双星的质量比分布。假设质量比分布的形式为在质量比为0.4处分段的双幂律再加大质量比双星超出组成,其中大质量比双星成分假设为在0.8~1之间的以1为中心的高斯分布形式。分别以有bin和无bin两种方式得到了质量比分布的最佳拟合,发现无bin的拟合效果更好。结果显示,对质量比小于0.4的部分,幂指数为-1.23±0.04;而质量比在0.4~0.8之间时幂指数为-4.52±0.07。这一结果表明,密近双星质量比分布与宽距双星的质量比分布在统计上并不相同,也不能用初始质量函数随机配对进行解释。这可能是因为密近双星经历了更复杂的动力学演化,从而改变了质量比分布的统计特征。

关键词：恒星双星质量比

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重大工程管理理论演化与发展路径

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系统管理学报 2018年第1期27卷 192-199页

作者：薛小龙王璐琪哈尔滨工业大学管理学院哈尔滨150001

重大工程是一类对我国政治、经济、社会、科技发展、环境保护、公众健康与国家安全具有重要影响的大型公共工程,有必要对其基础理论的形成与发展进行梳理,以更好地指导重大工程实践。重大工程管理理论与实践的差距为理论发展带来挑战和... 详细信息

重大工程是一类对我国政治、经济、社会、科技发展、环境保护、公众健康与国家安全具有重要影响的大型公共工程,有必要对其基础理论的形成与发展进行梳理,以更好地指导重大工程实践。重大工程管理理论与实践的差距为理论发展带来挑战和机遇。在分析科学理论形成及发展基本原理后,结合重大工程特点,总结重大工程管理理论形成过程。在重大工程历史演化基础上,分析重大工程管理理论评价的维度和标准,梳理重大工程管理理论5个发展阶段,指出当前重大工程管理理论发展仍处于理论累积阶段,据此构建以可持续为战略目标、智能化为战略路径、能力构建为实施保障的重大工程管理理论发展框架,为重大工程实践提供理论参考。

关键词：重大工程理论演化发展路径

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中国入境旅游市场的恢复与营销创新

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旅游学刊 2024年第4期39卷 9-10页

作者：陈晔王璐琪南开大学旅游与服务学院天津300071

一、中国入境旅游市场的现状近年来,我国入境旅游市场总体上呈现小幅增长的趋势。据原国家旅游局发布的《2016年中国旅游业统计公报》显示,2016年我国入境旅游人数为1.38亿人次。中国旅游研究院发布的《2019年旅游市场基本情况》显示,2... 详细信息

一、中国入境旅游市场的现状近年来,我国入境旅游市场总体上呈现小幅增长的趋势。据原国家旅游局发布的《2016年中国旅游业统计公报》显示,2016年我国入境旅游人数为1.38亿人次。中国旅游研究院发布的《2019年旅游市场基本情况》显示,2019年我国入境旅游人数达到了1.45亿人次。2020年初,由于新冠疫情的影响,我国入境旅游遭遇巨大冲击,几乎进入停滞状态。2023年,随着世界各国陆续放开跨境旅游市场,我国入境旅游有所恢复。

关键词：入境旅游市场营销创新市场基本情况跨境旅游统计公报国家旅游局我国入境旅游人数停滞状态

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