Global climate change is intensifying the impact of slope hazards,particularly rainfall-induced landslide hazards(RILH),on mountain road networks(MRNs).However,effective quantitative models for dynamically assessing M...Global climate change is intensifying the impact of slope hazards,particularly rainfall-induced landslide hazards(RILH),on mountain road networks(MRNs).However,effective quantitative models for dynamically assessing MRNs vulnerability under RILH disturbances are still lacking.To bridge this gap,this study develops a Cascading Failure Model for Rainfall-Induced Landslide Hazard(CFM-RILH).Validation via a case study of the GarzêTibetan Autonomous Prefecture Road Network(GTPRNs)reveals key characteristics of MRNs system vulnerability under RILH disturbances:(1)Under the disturbance effects of RILH,the vulnerability of the MRNs system follows a nonlinear phase transition law that intensifies with increasing disturbance intensity,exhibiting a distinct critical threshold.When the disturbance intensity exceeds this threshold,the system undergoes a global cascading failure phenomenon analogous to an“avalanche.”(2)Under RILH disturbances,the robustness of the MRNs system possesses a distinct safety boundary.Exceeding this boundary not only fails to improve hazard resistance but instead substantially elevates the risk of large-scale cascading failure.(3)Increasing network redundancy may be considered one of the primary engineering measures for enhancing MRNs resilience against such disturbances.Based on these findings,we propose a“Two-Stage Emergency Response and Hierarchical Fortification”strategy specifically to improve the resilience of GTPRNs impacted by RILH.The CFM-RILH model provides an effective tool for assessing road network vulnerability under such hazards.Furthermore,its modeling framework can also inform vulnerability assessment and resilience strategy development for road networks affected by other types of slope hazards.展开更多
Landslide susceptibility mapping of mountain roads is frequently confronted by insufficient historical landslide sample data,multicollinearity of existing evaluation index factors,and inconsistency of evaluation facto...Landslide susceptibility mapping of mountain roads is frequently confronted by insufficient historical landslide sample data,multicollinearity of existing evaluation index factors,and inconsistency of evaluation factors due to regional environmental variations.Then,a single machine learning model can easily become overfitting,thus reducing the accuracy and robustness of the evaluation model.This paper proposes a combined machine-learning model to address the issues.The landslide susceptibility in mountain roads were mapped by using factor analysis to normalize and reduce the dimensionality of the initial condition factor and generating six new combination factors as evaluation indexes.The mountain roads in the Youxi County,Fujian Province,China were used for the landslide susceptibility mapping.Three most frequently used machine learning techniques,support vector machine(SVM),random forest(RF),and artificial neural network(ANN)models,were used to model the landslide susceptibility of the study area and validate the accuracy of this evaluation index system.The global minimum variance portfolio was utilized to construct a machine learning combined model.5-fold cross-validation,statistical indexes,and AUC(Area Under Curve)values were implemented to evaluate the predictive accuracy of the landslide susceptibility model.The mean AUC values for the SVM,RF,and ANN models in the training stage were 89.2%,88.5%,and 87.9%,respectively,and 78.0%,73.7%,and 76.7%,respectively,in the validating stage.In the training and validation stages,the mean AUC values of the combined model were 92.4% and 87.1%,respectively.The combined model provides greater prediction accuracy and model robustness than one single model.展开更多
SONG Fangrong, the Tu nationality girl who grew up drinking water from mountain springs, walked into the Great Hall of the People in Beijing to accept the highest prize for China’s youth—the "May 4th Youth Priz...SONG Fangrong, the Tu nationality girl who grew up drinking water from mountain springs, walked into the Great Hall of the People in Beijing to accept the highest prize for China’s youth—the "May 4th Youth Prize." Not long before, she had been named one of the National Ten Outstanding Youths. She is the only individual to have won both.展开更多
Current situation of road landscaping in old districts of mountainous cities was analyzed,renovation design principles and basis were proposed. Pengshui County in Chongqing was taken for example to explore renovation ...Current situation of road landscaping in old districts of mountainous cities was analyzed,renovation design principles and basis were proposed. Pengshui County in Chongqing was taken for example to explore renovation design methods,overall concepts and relevant contents of the road landscaping in old districts of mountainous cities,so as to provide references for the renovation design of road landscaping in old districts of modern mountainous cities.展开更多
The settlement of widened highway subgrade in mountainous area is not only affected by the interaction between new and existing subgrade,but also seriously restricted by the external retaining wall.Based on the practi...The settlement of widened highway subgrade in mountainous area is not only affected by the interaction between new and existing subgrade,but also seriously restricted by the external retaining wall.Based on the practical engineering of half-filled and half-cut widened mountainous highway subgrade with external balance weight retaining wall(BWRW),a sophisticated finite element numerical model is established.The evolution law of subgrade settlement is revealed during the whole process of new subgrade filling and BWRW inclination after construction.The settlement component of subgrade is clarified considering whether the existing pavement continues to be used.The results show that the additional settlement caused by the BWRW inclination after construction cannot be ignored in the widening and reconstruction of mountainous highway subgrade.In addition,pursuant to the comprehensive design of subgrade and pavement,the component of subgrade settlement should be determined according to whether the existing pavement continues to be used,while considering the influence of BWRW inclination after construction.When the existing pavement continues to be used,the settlement of the existing subgrade is caused by the new subgrade filling and the BWRW inclination after construction.On the contrary,the settlement is only caused by the BWRW inclination after construction.展开更多
Taking the planning of elderly building for example, this paper explored the spatial layout, entrance/exit design, road space design and landscape design of the elderly residential districts against the background of ...Taking the planning of elderly building for example, this paper explored the spatial layout, entrance/exit design, road space design and landscape design of the elderly residential districts against the background of population aging and increasing demands of ecological residence. In addition, the paper tried to fully use outstanding natural environment in mountainous areas to plan the elderly community, and integrate the characteristics of mountainous community planning and elderly buildings.展开更多
为探究山区双车道公路行驶车辆的超车行为特性,基于无人机高空拍摄的超车行为视频数据,提出一种基于随机生存森林的超车持续时间预测模型.首先,利用Tracker软件提取超车行为相关车辆的行驶轨迹,并对超车行为特征进行分析;其次,采用非参...为探究山区双车道公路行驶车辆的超车行为特性,基于无人机高空拍摄的超车行为视频数据,提出一种基于随机生存森林的超车持续时间预测模型.首先,利用Tracker软件提取超车行为相关车辆的行驶轨迹,并对超车行为特征进行分析;其次,采用非参数Kaplan-Meier模型和全参数加速失效时间(Accelerated Failure Time, AFT)模型确定影响超车持续时间的关键协变量;最后,构建随机生存森林模型预测山区双车道公路的超车持续时间.结果表明:山区双车道公路平均超车持续时间为12.3 s,考虑超车类型的超车持续时间在无对向来车时表现出显著差异;相较于固定效应AFT模型,全参数AFT模型具有更好的拟合优度,超车距离、超车车辆最终速度、被超车辆类型是影响超车持续时间的关键变量;对比随机森林模型、生存支持向量模型、XG-Boost模型,随机生存森林模型在一致性指数和整合布里尔分数等方面均优于前三者,且考虑超车类型对山区双车道公路超车持续时间的预测效果影响较小;根据变量重要性排名,超车距离和两车的初始速度差对超车持续时间的影响较大.研究结果可为提高山区公路行车安全提供参考.展开更多
为实现黏滞效应影响下的车速准确预测,以云南省典型山区公路穿村镇段为例,基于无人机拍摄视频提取的行车轨迹数据,引入流体力学定义黏滞效应的作用机制,并构建黏滞系数测度模型,将黏滞系数与基于注意力机制的门控循环单元(Gate Recurren...为实现黏滞效应影响下的车速准确预测,以云南省典型山区公路穿村镇段为例,基于无人机拍摄视频提取的行车轨迹数据,引入流体力学定义黏滞效应的作用机制,并构建黏滞系数测度模型,将黏滞系数与基于注意力机制的门控循环单元(Gate Recurrent Unit based on Attention Mechanism,GRU-AM)模型相结合,提出了考虑黏滞效应的山区公路穿村镇段车辆速度预测方法并验证其有效性。结果表明,黏滞效应导致车流呈现近似流体的黏滞性假设成立,山区公路穿村镇段车辆运行速度特性呈“低车速、高离散”现象,其速度25%、50%、85%分位值与普通路段的差值分别为-2.01 m/s、-1.68 m/s、-1.35 m/s,速度变异系数、速度离散系数的差值分别为0.058、0.218。此外,将黏滞系数作为关键输入特征提高了预测模型的准确性,构建的GRU-AM模型拟合优度(R2)提高了2.57百分点、平均绝对误差(Mean Absolute Error,MAE)减小了0.188,用于对比的单一模型门控循环单元(Gate Recurrent Unit,GRU)和Transformer的R2分别提高了3.88百分点和9.89百分点、MAE分别减小了0.1075和0.2344,其中GRU-AM模型表现最好,R2为95.23%,MAE为0.4352。研究表明,考虑黏滞效应的山区公路穿村镇段车速预测方法具有良好的预测性能。展开更多
基金financially supported by the National Key R&D Program of China(2024YFE0111900)The National Natural Science Foundation of China(U2468214,52378370,52278372)+1 种基金The National Ten Thousand Talent Program for Young Top-notch Talents(2022QB04978)The Science and Technology Program of Hebei Province(2023HBQZYCSB004)。
文摘Global climate change is intensifying the impact of slope hazards,particularly rainfall-induced landslide hazards(RILH),on mountain road networks(MRNs).However,effective quantitative models for dynamically assessing MRNs vulnerability under RILH disturbances are still lacking.To bridge this gap,this study develops a Cascading Failure Model for Rainfall-Induced Landslide Hazard(CFM-RILH).Validation via a case study of the GarzêTibetan Autonomous Prefecture Road Network(GTPRNs)reveals key characteristics of MRNs system vulnerability under RILH disturbances:(1)Under the disturbance effects of RILH,the vulnerability of the MRNs system follows a nonlinear phase transition law that intensifies with increasing disturbance intensity,exhibiting a distinct critical threshold.When the disturbance intensity exceeds this threshold,the system undergoes a global cascading failure phenomenon analogous to an“avalanche.”(2)Under RILH disturbances,the robustness of the MRNs system possesses a distinct safety boundary.Exceeding this boundary not only fails to improve hazard resistance but instead substantially elevates the risk of large-scale cascading failure.(3)Increasing network redundancy may be considered one of the primary engineering measures for enhancing MRNs resilience against such disturbances.Based on these findings,we propose a“Two-Stage Emergency Response and Hierarchical Fortification”strategy specifically to improve the resilience of GTPRNs impacted by RILH.The CFM-RILH model provides an effective tool for assessing road network vulnerability under such hazards.Furthermore,its modeling framework can also inform vulnerability assessment and resilience strategy development for road networks affected by other types of slope hazards.
基金the financial support from the National Natural Science Foundation of China(No.U2005205,No.42007235,No.41972268)the Science and Technology Innovation Platform Project of Fuzhou Science and Technology Bureau(No.2021-P-032)。
文摘Landslide susceptibility mapping of mountain roads is frequently confronted by insufficient historical landslide sample data,multicollinearity of existing evaluation index factors,and inconsistency of evaluation factors due to regional environmental variations.Then,a single machine learning model can easily become overfitting,thus reducing the accuracy and robustness of the evaluation model.This paper proposes a combined machine-learning model to address the issues.The landslide susceptibility in mountain roads were mapped by using factor analysis to normalize and reduce the dimensionality of the initial condition factor and generating six new combination factors as evaluation indexes.The mountain roads in the Youxi County,Fujian Province,China were used for the landslide susceptibility mapping.Three most frequently used machine learning techniques,support vector machine(SVM),random forest(RF),and artificial neural network(ANN)models,were used to model the landslide susceptibility of the study area and validate the accuracy of this evaluation index system.The global minimum variance portfolio was utilized to construct a machine learning combined model.5-fold cross-validation,statistical indexes,and AUC(Area Under Curve)values were implemented to evaluate the predictive accuracy of the landslide susceptibility model.The mean AUC values for the SVM,RF,and ANN models in the training stage were 89.2%,88.5%,and 87.9%,respectively,and 78.0%,73.7%,and 76.7%,respectively,in the validating stage.In the training and validation stages,the mean AUC values of the combined model were 92.4% and 87.1%,respectively.The combined model provides greater prediction accuracy and model robustness than one single model.
文摘SONG Fangrong, the Tu nationality girl who grew up drinking water from mountain springs, walked into the Great Hall of the People in Beijing to accept the highest prize for China’s youth—the "May 4th Youth Prize." Not long before, she had been named one of the National Ten Outstanding Youths. She is the only individual to have won both.
文摘Current situation of road landscaping in old districts of mountainous cities was analyzed,renovation design principles and basis were proposed. Pengshui County in Chongqing was taken for example to explore renovation design methods,overall concepts and relevant contents of the road landscaping in old districts of mountainous cities,so as to provide references for the renovation design of road landscaping in old districts of modern mountainous cities.
基金supported by Sichuan Science and Technology Program(No.2019YFS0492)Key Laboratories Open Engineering Practice Program to Undergraduates of SWJTU(No.ZD2020010010)。
文摘The settlement of widened highway subgrade in mountainous area is not only affected by the interaction between new and existing subgrade,but also seriously restricted by the external retaining wall.Based on the practical engineering of half-filled and half-cut widened mountainous highway subgrade with external balance weight retaining wall(BWRW),a sophisticated finite element numerical model is established.The evolution law of subgrade settlement is revealed during the whole process of new subgrade filling and BWRW inclination after construction.The settlement component of subgrade is clarified considering whether the existing pavement continues to be used.The results show that the additional settlement caused by the BWRW inclination after construction cannot be ignored in the widening and reconstruction of mountainous highway subgrade.In addition,pursuant to the comprehensive design of subgrade and pavement,the component of subgrade settlement should be determined according to whether the existing pavement continues to be used,while considering the influence of BWRW inclination after construction.When the existing pavement continues to be used,the settlement of the existing subgrade is caused by the new subgrade filling and the BWRW inclination after construction.On the contrary,the settlement is only caused by the BWRW inclination after construction.
基金Sponsored by National Youth Science Foundation(51408507)China Postdoctoral Science Foundation(2015M570385)
文摘Taking the planning of elderly building for example, this paper explored the spatial layout, entrance/exit design, road space design and landscape design of the elderly residential districts against the background of population aging and increasing demands of ecological residence. In addition, the paper tried to fully use outstanding natural environment in mountainous areas to plan the elderly community, and integrate the characteristics of mountainous community planning and elderly buildings.
文摘为探究山区双车道公路行驶车辆的超车行为特性,基于无人机高空拍摄的超车行为视频数据,提出一种基于随机生存森林的超车持续时间预测模型.首先,利用Tracker软件提取超车行为相关车辆的行驶轨迹,并对超车行为特征进行分析;其次,采用非参数Kaplan-Meier模型和全参数加速失效时间(Accelerated Failure Time, AFT)模型确定影响超车持续时间的关键协变量;最后,构建随机生存森林模型预测山区双车道公路的超车持续时间.结果表明:山区双车道公路平均超车持续时间为12.3 s,考虑超车类型的超车持续时间在无对向来车时表现出显著差异;相较于固定效应AFT模型,全参数AFT模型具有更好的拟合优度,超车距离、超车车辆最终速度、被超车辆类型是影响超车持续时间的关键变量;对比随机森林模型、生存支持向量模型、XG-Boost模型,随机生存森林模型在一致性指数和整合布里尔分数等方面均优于前三者,且考虑超车类型对山区双车道公路超车持续时间的预测效果影响较小;根据变量重要性排名,超车距离和两车的初始速度差对超车持续时间的影响较大.研究结果可为提高山区公路行车安全提供参考.
文摘为实现黏滞效应影响下的车速准确预测,以云南省典型山区公路穿村镇段为例,基于无人机拍摄视频提取的行车轨迹数据,引入流体力学定义黏滞效应的作用机制,并构建黏滞系数测度模型,将黏滞系数与基于注意力机制的门控循环单元(Gate Recurrent Unit based on Attention Mechanism,GRU-AM)模型相结合,提出了考虑黏滞效应的山区公路穿村镇段车辆速度预测方法并验证其有效性。结果表明,黏滞效应导致车流呈现近似流体的黏滞性假设成立,山区公路穿村镇段车辆运行速度特性呈“低车速、高离散”现象,其速度25%、50%、85%分位值与普通路段的差值分别为-2.01 m/s、-1.68 m/s、-1.35 m/s,速度变异系数、速度离散系数的差值分别为0.058、0.218。此外,将黏滞系数作为关键输入特征提高了预测模型的准确性,构建的GRU-AM模型拟合优度(R2)提高了2.57百分点、平均绝对误差(Mean Absolute Error,MAE)减小了0.188,用于对比的单一模型门控循环单元(Gate Recurrent Unit,GRU)和Transformer的R2分别提高了3.88百分点和9.89百分点、MAE分别减小了0.1075和0.2344,其中GRU-AM模型表现最好,R2为95.23%,MAE为0.4352。研究表明,考虑黏滞效应的山区公路穿村镇段车速预测方法具有良好的预测性能。
