Query：
学者姓名：林川
Refining：
Year
Type
Indexed by
Source
Complex
Co-
Language
Clean All
Abstract ：
Detecting water head is crucial in groundwater utilization, and requires quick and accurate solutions. This study employs a method combining the collocation Trefftz method (CTM) and the fictitious time integration method (FTIM) for groundwater head detection and restoration. The Laplace equation is solved using CTM, and the Trefftz basis function is linearly combined to fit the exact solution while adding characteristics length for numerical stability. The FTIM solves the nonlinear algebraic equations system for water head detection. Numerical examples quantify the method's accuracy, and boundary restoration results are compared with the Picard successive approximation method, showcasing FTIM's advantages in convergence steps and precision. The solution comparison under irregular boundary conditions further verifies the proposed method's efficacy (MAE <= 10-15). The CTM-FTIM calculated water level boundary aligns with the actual boundary, and its noise immunity is verified using real observation well data (MAE <= 10-2, Itertimes <= 5000). The CTM-FTIM method eliminates meshing needs for quick solutions in irregular regions, accurately determining water levels in the study domain using few known boundary points, solving infinite domain groundwater head detection.
Keyword ：
Fictitious time integration method Fictitious time integration method Groundwater head detection recovery Groundwater head detection recovery Noise immunity Noise immunity Observation well data Observation well data Trefftz method Trefftz method
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Su, Yan , Huang, Bin , Yang, Lingjun et al. Study on the detection of groundwater boundary based on the Trefftz method [J]. | NATURAL HAZARDS , 2024 . |
| MLA | Su, Yan et al. "Study on the detection of groundwater boundary based on the Trefftz method" . | NATURAL HAZARDS (2024) . |
| APA | Su, Yan , Huang, Bin , Yang, Lingjun , Lai, Xiaohe , Lin, Chuan , Xie, Xiudong et al. Study on the detection of groundwater boundary based on the Trefftz method . | NATURAL HAZARDS , 2024 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
考虑到滑坡编录制作的耗时性,建立一种"可迁移"的滑坡易发性模型已越发重要.合理利用现有完整滑坡数据地区的样本集对无样本区域进行易发性预测具有重要意义.运用迁移成分分析(transfer component analysis,TCA)方法,结合深度学习卷积神经网络(convolutional neural network,CNN),尝试引入一种基于迁移学习域自适应方法的TCA-CNN模型,并以福建省两个库岸地区为例,提取 11个库岸相关环境因子建立滑坡空间数据库,将有样本的池潭库区易发性模型迁移至无样本的棉花滩库区进行预测,实现跨区域滑坡易发性评价.通过对棉花滩库区进行易发性预测,结果显示:(1)采用TCA方法处理后的不同研究区数据最大均值差异(maximize mean discrepancy,MMD)明显降低(0.022),数据实现近似同分布;(2)TCA-CNN模型的跨区域预测精度为 0.854,高于CNN模型(0.791),且通过历史滑坡验证其落入高、极高易发性区间的滑坡频率比占比最高(89.1%);(3)受试者工作特性(receiver operating characteristic,ROC)曲线下面积TCA-CNN模型为 0.93,高于CNN模型的 0.90.可见TCA-CNN模型能够有效运用建模区的样本数据实现对无样本区域的易发性评价,且相比于传统机器模型在进行跨区域预测时具有更高、更稳定的预测准确率,具备更强的泛化能力.
Keyword ：
卷积神经网络 卷积神经网络 库岸边坡 库岸边坡 数据缺失 数据缺失 滑坡 滑坡 滑坡易发性 滑坡易发性 灾害 灾害 迁移成分分析 迁移成分分析
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | 苏燕 , 黄绍翔 , 赖晓鹤 et al. 基于迁移成分分析的库岸跨区域滑坡易发性评价 [J]. | 地球科学 , 2024 , 49 (5) : 1636-1653 . |
| MLA | 苏燕 et al. "基于迁移成分分析的库岸跨区域滑坡易发性评价" . | 地球科学 49 . 5 (2024) : 1636-1653 . |
| APA | 苏燕 , 黄绍翔 , 赖晓鹤 , 陈耀鑫 , 杨凌鋆 , 林川 et al. 基于迁移成分分析的库岸跨区域滑坡易发性评价 . | 地球科学 , 2024 , 49 (5) , 1636-1653 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
Given the time-consuming nature of compiling landslide inventories, it is increasingly important to develop transferable landslide susceptibility models that can be applied to regions without existing data. In this study, we propose a feature-based domain adaptation method to improve the transferability of landslide susceptibility models, especially in "no sample" areas. Two typical landslide-prone areas in Fujian province, southeastern China, were chosen as research cases to test the practicality of the transfer effect. Five conventional machine learning algorithms (Support vector machines (SVM), Random Forest (RF), Logistic Regression (LOG), K-nearest neighbor (KNN), and Decision tree (C4.5)) are used to model landslide susceptibility in sampled areas (source domain), and a feature transfer-based landslide susceptibility evaluation model is constructed under coupled feature transfer methods to evaluate the susceptibility of landslide in un-sampled areas (target domain). The results showed that feature transfer can effectively improve the transferability of different machine learning models for cross-regional prediction (The indicators have improved overall by 8.49%), with SVM (increased by 13.68%) and LOG (increased by 10.19%) models showing the most significant improvements. The feature-based domain adaptive method can alleviate the burden of collecting and labeling new data, and effectively improve the assessment performance of machine learning-based landslide susceptibility models in un-sampled areas. This is a new solution for landslide susceptibility assessment in completely "no sample" areas. (c) 2024 International Association for Gondwana Research. Published by Elsevier B.V. All rights reserved.
Keyword ：
Data scarcity Data scarcity Feature domain adaptation Feature domain adaptation Landslide susceptibility Landslide susceptibility Machine learning Machine learning Reservoir bank slope Reservoir bank slope
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Su, Yan , Chen, Yaoxin , Lai, Xiaohe et al. Feature adaptation for landslide susceptibility assessment in "no sample" areas [J]. | GONDWANA RESEARCH , 2024 , 131 : 1-17 . |
| MLA | Su, Yan et al. "Feature adaptation for landslide susceptibility assessment in "no sample" areas" . | GONDWANA RESEARCH 131 (2024) : 1-17 . |
| APA | Su, Yan , Chen, Yaoxin , Lai, Xiaohe , Huang, Shaoxiang , Lin, Chuan , Xie, Xiudong . Feature adaptation for landslide susceptibility assessment in "no sample" areas . | GONDWANA RESEARCH , 2024 , 131 , 1-17 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
山体滑坡是全球范围内多发的一种地质灾害.由于滑坡具有突发性和破坏性强的特点,建立有效的数值分析模型将有助于制定针对性的防治策略.本文针对滑坡运动过程中表现出的颗粒流特性,基于 μ(I)模型提出了针对浅层滑坡的动态摩擦系数表达式,并构建了对应的光滑粒子流体动力学(SPH)方法求解框架.考虑到颗粒破碎对滑坡运动性的显著影响,结合基于破坏势能的颗粒破碎法则,建立 μ(I)模型中基底摩擦力与颗粒分布之间的关系.通过两个经典的三维斜面模型试验,验证了 μ(I)模型在滑坡运动分析中的应用价值,并进行了颗粒破碎效应参数敏感性分析,为后续滑坡灾害的防治工作提供参考.
Keyword ：
μ(I)模型 μ(I)模型 光滑粒子流体动力学 光滑粒子流体动力学 滑坡 滑坡 颗粒破碎 颗粒破碎
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | 林川 , 林彦喆 , 苏燕 et al. 颗粒流运动SPH方法及滑坡破碎效应研究 [J]. | 水力发电学报 , 2024 , 43 (7) : 61-72 . |
| MLA | 林川 et al. "颗粒流运动SPH方法及滑坡破碎效应研究" . | 水力发电学报 43 . 7 (2024) : 61-72 . |
| APA | 林川 , 林彦喆 , 苏燕 , 潘依琳 , 高献 . 颗粒流运动SPH方法及滑坡破碎效应研究 . | 水力发电学报 , 2024 , 43 (7) , 61-72 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
Understanding the evolution and driving factors of sedimentation and erosion at the mouths of small and medium-sized mountain streams during various periods is essential for regional spatial utilization, development, and sustainable economic growth. This is particularly important when considering the combined impact of climate change and human activities. This paper presents an analysis of the changes in sedimentation and erosion of mouth isobaths and underwater deltas over different periods using nautical chart data (1950-2019) and analyzes the factors driving changes in sedimentation and erosion during different periods from 1950 to 2020 based on the runoff-sediment discharge of the Minjiang River (MR) and extreme climate factors such as typhoons, especially the driving factors that caused a sudden change in the sedimentation and erosion process between 1998 and 2005. The results indicate that runoff-sediment characteristics are crucial in driving sedimentation and erosion changes. In the past 70 years, the underwater delta of the MRE has mainly experienced four stages: deposition (1950-1992) -erosion (1993-1998) -deposition (1998-2011) -erosion (2011-2019). Taking the impoundment operation of the Shuikou Reservoir in 1993 as the node, the sediment load of the Minjiang River into the sea began to decrease sharply, and then the estuary quickly showed a state of erosion. The change of sediment flux into the sea is the main driving factor for the evolution of erosion and deposition in the Minjiang River Estuary (MRE). The critical value of the erosion-deposition transition is about 570.3 x 104 t/yr. After the estuary entered a state of erosion in 1993-1998, significant siltation suddenly occurred in 1998-2005. The reason for the siltation in this period may be related to the frequent transit typhoons and flood events in 1998-2005. Therefore, the change of river sediment supply into the sea is the main driving factor controlling the erosion and deposition evolution of the Minjiang River estuary on a long time scale of more than 10 years, which reflects the influence of large-scale human activities on the river and estuary area in the past half century. Extreme climate events are the incentive to adjust the estuary landform in the short term. Extreme climate events will not fundamentally change the process of estuarine geomorphological evolution under the background of sediment supply reduction.
Keyword ：
driving factors driving factors extreme climate extreme climate human activities human activities Minjiang River estuary Minjiang River estuary sediment sediment
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Lai, Xiaohe , Jia, Jianping , Hou, Yuebao et al. Analysis of the driving factors of the change of erosion-deposition in the Minjiang Estuary, Southeast China [J]. | FRONTIERS IN MARINE SCIENCE , 2023 , 10 . |
| MLA | Lai, Xiaohe et al. "Analysis of the driving factors of the change of erosion-deposition in the Minjiang Estuary, Southeast China" . | FRONTIERS IN MARINE SCIENCE 10 (2023) . |
| APA | Lai, Xiaohe , Jia, Jianping , Hou, Yuebao , Jiang, Beihan , Lin, Chuan , Lin, Xinlu et al. Analysis of the driving factors of the change of erosion-deposition in the Minjiang Estuary, Southeast China . | FRONTIERS IN MARINE SCIENCE , 2023 , 10 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
Debris flows can be considered a type of landslide with large velocities and long run-out distances. There are many types of debris flows, depending on the properties of the solid and fluid components of the mixture. The triggering and propagation of debris flows can be studied using a single 3D mathematical model. The computational cost can be very high because of their length, and depth-integrated models provide a good combination of accuracy and cost. Both types of models can be combined in the analysis, using 3D models for initiation and at singular points where more accuracy is wanted. As in a chain where the strength is never higher than that of the weaker link, we have to ensure that all the models are accurate enough in a joint model. This paper deals with a new depth-integrated model which can take into account the changes caused by dewatering in a debris flow. An important limitation of existing two-phase models allowing different velocities of solid and water particles is that when water abandons the mixture, porosity decreases and tends to zero. Here, a two-layer model is introduced, including an unsaturated upper layer on top of a saturated layer.
Keyword ：
Depth integrated model Depth integrated model Desaturation Desaturation Permeable drainage Permeable drainage SPH SPH Two phases Two phases
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Pastor, Manuel , Tayyebi, Saeid Moussavi , Hernandez, Andrei et al. A new two-layer two-phase depth-integrated SPH model implementing dewatering: Application to debris flows [J]. | COMPUTERS AND GEOTECHNICS , 2023 , 153 . |
| MLA | Pastor, Manuel et al. "A new two-layer two-phase depth-integrated SPH model implementing dewatering: Application to debris flows" . | COMPUTERS AND GEOTECHNICS 153 (2023) . |
| APA | Pastor, Manuel , Tayyebi, Saeid Moussavi , Hernandez, Andrei , Gao, Lingang , Stickle, Miguel Martin , Lin, Chuan . A new two-layer two-phase depth-integrated SPH model implementing dewatering: Application to debris flows . | COMPUTERS AND GEOTECHNICS , 2023 , 153 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
在降雨过程中，潜在的泥石流触发体在水文地质作用的影响下，会形成泥石流，对下游人们的生命财产安全造成严重威胁。构建有效的泥石流监测预警预报系统是减小灾害影响的有效手段。针对现有预警系统只能提供泥石流触发与否或触发风险高低的结果，研究出了机器学习和光滑粒子流体动力学（Smoothed Particle Hydrodynamics,SPH）方法联合驱动的泥石流预警系统，对泥石流触发后可能的影响范围和灾害烈度进行全面评估，实现了对泥石流灾害的精细化预警，可以有效减少泥石流灾害的影响和危害。
Keyword ：
SPH模型 SPH模型 决策树 决策树 泥石流 泥石流 预警系统 预警系统
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | 林辰怿 , 甘娇女 , 潘依琳 et al. 机器学习和SPH方法联合驱动的泥石流预警系统研究 [J]. | 甘肃水利水电技术 , 2023 , 59 (05) : 30-33 . |
| MLA | 林辰怿 et al. "机器学习和SPH方法联合驱动的泥石流预警系统研究" . | 甘肃水利水电技术 59 . 05 (2023) : 30-33 . |
| APA | 林辰怿 , 甘娇女 , 潘依琳 , 冯华青 , 张萌杰 , 刘英杰 et al. 机器学习和SPH方法联合驱动的泥石流预警系统研究 . | 甘肃水利水电技术 , 2023 , 59 (05) , 30-33 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
混凝土面板堆石坝变形测值具有高度的非线性和复杂性，变形影响因素众多且因素间存在多重共线性。针对此类坝型的变形预测分析问题，本文提出一种基于因子融合的混凝土面板堆石坝变形预测模型。首先，利用变分模态分解对变形时间序列进行分解，有效降低变形时间序列的复杂程度，提升特征提取效果。随后，借助偏最小二乘回归对变形影响因子进行降维融合，降低自变量间多重共线性对构建模型的影响，提高模型可解释性。最后，通过一维卷积网络融合门控循环单元神经网络对子序列进行重构预测。根据实际工程分析结果，本模型可以在效率和精度上有效提升混凝土面板堆石坝变形预测效果，对类似坝型的变形监测分析具有一定的参考意义。
Keyword ：
偏最小二乘法 偏最小二乘法 变分模态分解 变分模态分解 大坝变形预测 大坝变形预测 深度学习 深度学习 混凝土面板堆石坝 混凝土面板堆石坝
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | 林川 , 桂星煜 , 朱律运 et al. 基于因子融合的混凝土面板堆石坝变形预测模型 [J]. | 水力发电学报 , 2023 , 42 (10) : 139-152 . |
| MLA | 林川 et al. "基于因子融合的混凝土面板堆石坝变形预测模型" . | 水力发电学报 42 . 10 (2023) : 139-152 . |
| APA | 林川 , 桂星煜 , 朱律运 , 苏燕 , 林梦婧 , 唐燕芳 et al. 基于因子融合的混凝土面板堆石坝变形预测模型 . | 水力发电学报 , 2023 , 42 (10) , 139-152 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
针对大坝变形时间序列预测问题，考虑多测点变形相关性，建立变形量时空多维输入矩阵，提出一种基于K-means聚类融合多元时空信息的Informer-AD大坝变形预测模型。首先，采用K-means聚类对变形测点进行分区；其次，引入面板数据回归模型分析分区结果；最后，提出融合多元时空信息的Informer-AD大坝变形预测模型。利用该模型对空间特征序列进行学习，通过全连接层整合空间特征，输出预测的大坝变形值。将上述预测模型运用于CT混凝土重力坝，结果表明，本文所提出的考虑时空关联性的预测方法充分挖掘大坝变形整体性态与测点空间分布特性的关系，能够更好地捕捉变形时空特性，进而提高预测精度。
Keyword ：
Informer-AD Informer-AD K-means聚类 K-means聚类 大坝变形预测 大坝变形预测 时空相关特性 时空相关特性 深度学习 深度学习
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | 苏燕 , 黄姝璇 , 林川 et al. 融合多元时空信息的Informer-AD大坝变形预测模型 [J]. | 水力发电学报 , 2023 , 42 (11) : 101-113 . |
| MLA | 苏燕 et al. "融合多元时空信息的Informer-AD大坝变形预测模型" . | 水力发电学报 42 . 11 (2023) : 101-113 . |
| APA | 苏燕 , 黄姝璇 , 林川 , 李伊璇 , 付家源 , 郑志铭 . 融合多元时空信息的Informer-AD大坝变形预测模型 . | 水力发电学报 , 2023 , 42 (11) , 101-113 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
The deformation behavior of a dam can comprehensively reflect its structural state. By comparing the actual response with model predictions, dam deformation prediction models can detect anomalies for effective advance warning. Most existing dam deformation prediction models are implemented within a single-step prediction framework; the single-time-step output of these models cannot represent the variation trend in the dam deformation, which may contain important information on dam evolution during the prediction period. Compared with the single value prediction, predicting the tendency of dam deformation in the short term can better interpret the dam's structural health status. Aiming to capture the short-term variation trends of dam deformation, a multi-step displacement prediction model of concrete dams is proposed by combining the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm, the k-harmonic means (KHM) algorithm, and the error minimized extreme learning machine (EM-ELM) algorithm. The model can be divided into three stages: (1) The CEEMDAN algorithm is adopted to decompose dam displacement series into different signals according to their timing characteristics. Moreover, the sample entropy (SE) method is used to remove the noise contained in the decomposed signals. (2) The KHM clustering algorithm is employed to cluster the denoised data with similar characteristics. Furthermore, the sparrow search algorithm (SSA) is utilized to optimize the KHM algorithm to avoid the local optimal problem. (3) A multi-step prediction model to capture the short-term variation of dam displacement is established based on the clustered data. Engineering examples show that the model has good prediction performance and strong robustness, demonstrating the feasibility of applying the proposed model to the multi-step forecasting of dam displacement.
Keyword ：
complete ensemble empirical mode decomposition with adaptive noise complete ensemble empirical mode decomposition with adaptive noise concrete dams concrete dams dam deformation dam deformation K-harmonic means K-harmonic means multi-step prediction multi-step prediction sparrow search algorithm sparrow search algorithm
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Lin, Chuan , Zou, Yun , Lai, Xiaohe et al. Variation Trend Prediction of Dam Displacement in the Short-Term Using a Hybrid Model Based on Clustering Methods [J]. | APPLIED SCIENCES-BASEL , 2023 , 13 (19) . |
| MLA | Lin, Chuan et al. "Variation Trend Prediction of Dam Displacement in the Short-Term Using a Hybrid Model Based on Clustering Methods" . | APPLIED SCIENCES-BASEL 13 . 19 (2023) . |
| APA | Lin, Chuan , Zou, Yun , Lai, Xiaohe , Wang, Xiangyu , Su, Yan . Variation Trend Prediction of Dam Displacement in the Short-Term Using a Hybrid Model Based on Clustering Methods . | APPLIED SCIENCES-BASEL , 2023 , 13 (19) . |
| Export to | NoteExpress RIS BibTex |
Version ：
Export
| Results： |
Selected to |
| Format： |
