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基于机器学习模型的高植被覆盖区浅层滑坡预测.
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- Transactions of the Chinese Society of Agricultural Engineering, 2024, v. 40, n. 17, p. 149, doi. 10.11975/j.issn.1002-6819.202312058
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Exploring time series models for landslide prediction: a literature review.
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- Geoenvironmental Disasters, 2024, v. 11, n. 1, p. 1, doi. 10.1186/s40677-024-00288-3
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Temporal clustering of precipitation for detection of potential landslides.
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- Natural Hazards & Earth System Sciences, 2024, v. 24, n. 8, p. 2689, doi. 10.5194/nhess-24-2689-2024
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Groundwater Level Prediction for Landslides Using an Improved TANK Model Based on Big Data.
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- Water (20734441), 2024, v. 16, n. 16, p. 2286, doi. 10.3390/w16162286
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Ensemble Predictions of Rainfall-Induced Landslide Risk under Climate Change in China Integrating Antecedent Soil-Wetness Factors.
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- Atmosphere, 2024, v. 15, n. 8, p. 1013, doi. 10.3390/atmos15081013
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- Article
基于元学习的广域范围滑坡易发性小样本预测.
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- Geomatics & Information Science of Wuhan University, 2024, v. 49, n. 8, p. 1367, doi. 10.13203/j.whugis20220076
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基于样本优化策略的滑坡易发性评价.
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- Geomatics & Information Science of Wuhan University, 2024, v. 49, n. 8, p. 1492, doi. 10.13203/j.whugis20220527
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考虑时间滞后效应的库岸滑坡位移预测.
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- Geomatics & Information Science of Wuhan University, 2024, v. 49, n. 8, p. 1347, doi. 10.13203/j.whugis20220133
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Examining the Controls on the Spatial Distribution of Landslides Triggered by the 2008 Wenchuan Ms 8.0 Earthquake, China, Using Methods of Spatial Point Pattern Analysis.
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- Sustainability (2071-1050), 2024, v. 16, n. 16, p. 6974, doi. 10.3390/su16166974
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Deformation evaluation and displacement forecasting of baishuihe landslide after stabilization based on continuous wavelet transform and deep learning.
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- Natural Hazards, 2024, v. 120, n. 11, p. 9649, doi. 10.1007/s11069-024-06580-7
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- Article
Assessing framework of rainfall-induced landslide hazard considering spatiotemporal asymmetry in extreme precipitation indices under climate change.
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- Theoretical & Applied Climatology, 2024, v. 155, n. 8, p. 7961, doi. 10.1007/s00704-024-05106-2
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Extraction of Spatiotemporal Information of Rainfall-Induced Landslides from Remote Sensing.
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- Remote Sensing, 2024, v. 16, n. 16, p. 3089, doi. 10.3390/rs16163089
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Application of Artificial Intelligence and Remote Sensing for Landslide Detection and Prediction: Systematic Review.
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- Remote Sensing, 2024, v. 16, n. 16, p. 2947, doi. 10.3390/rs16162947
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Stacking ensemble approach in data mining methods for landslide prediction.
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- Journal of Supercomputing, 2023, v. 79, n. 8, p. 8583, doi. 10.1007/s11227-022-05006-0
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基于变权重组合预测模型的堆积层滑坡稳定性评价分析.
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- Fly Ash Comprehensive Utilization, 2023, v. 37, n. 4, p. 134, doi. 10.19860/j.cnki.issn1005-8249.2023.04.022
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Complex sliding characteristics of landslides and evaluation of the reinforcement with arched anti-slide piles based on 3D discrete element method: a case study.
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- Natural Hazards, 2024, v. 120, n. 9, p. 8983, doi. 10.1007/s11069-024-06564-7
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Landslide development and susceptibility along the Yunling–Yanjing segment of the Lancang River using grid and slope units.
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- Natural Hazards, 2024, v. 120, n. 7, p. 6149, doi. 10.1007/s11069-024-06495-3
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Prediction of rainfall-induced landslide using machine learning models along highway Bandipora to Gurez road, India.
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- Natural Hazards, 2024, v. 120, n. 7, p. 6169, doi. 10.1007/s11069-024-06405-7
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Toward the reliable prediction of reservoir landslide displacement using earthworm optimization algorithm-optimized support vector regression (EOA-SVR).
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- Natural Hazards, 2024, v. 120, n. 4, p. 3165, doi. 10.1007/s11069-023-06322-1
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Integrated deep learning with explainable artificial intelligence for enhanced landslide management.
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- Natural Hazards, 2024, v. 120, n. 2, p. 1343, doi. 10.1007/s11069-023-06260-y
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On the estimation of landslide intensity, hazard and density via data-driven models.
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- Natural Hazards, 2023, v. 119, n. 3, p. 1513, doi. 10.1007/s11069-023-06153-0
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An innovative method for landslide susceptibility mapping supported by fractal theory, GeoDetector, and random forest: a case study in Sichuan Province, SW China.
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- Natural Hazards, 2023, v. 118, n. 3, p. 2543, doi. 10.1007/s11069-023-06104-9
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Prediction of landslide hazards induced by potential earthquake in Litang County, Sichuan, China.
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- Natural Hazards, 2023, v. 118, n. 2, p. 1301, doi. 10.1007/s11069-023-06050-6
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Patterns of influence of different landslide boundaries and their spatial shapes on the uncertainty of landslide susceptibility prediction.
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- Natural Hazards, 2023, v. 118, n. 1, p. 709, doi. 10.1007/s11069-023-06025-7
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Spatial and temporal landslide distributions using global and open landslide databases.
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- Natural Hazards, 2023, v. 117, n. 1, p. 25, doi. 10.1007/s11069-023-05848-8
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Development of a universal landslide hazard potential model for mudrock slopes: fuzzy logic and molecular-level modelling approaches.
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- Natural Hazards, 2023, v. 116, n. 3, p. 3583, doi. 10.1007/s11069-023-05826-0
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Landslide hazard and susceptibility maps derived from satellite and remote sensing data using limit equilibrium analysis and machine learning model.
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- Natural Hazards, 2023, v. 116, n. 1, p. 235, doi. 10.1007/s11069-022-05671-7
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Using distributed root soil moisture data to enhance the performance of rainfall thresholds for landslide warning.
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- Natural Hazards, 2023, v. 115, n. 2, p. 1167, doi. 10.1007/s11069-022-05588-1
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Machine learning and landslide studies: recent advances and applications.
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- Natural Hazards, 2022, v. 114, n. 2, p. 1197, doi. 10.1007/s11069-022-05423-7
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A hybrid deep learning method for landslide susceptibility analysis with the application of InSAR data.
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- Natural Hazards, 2022, v. 114, n. 2, p. 1393, doi. 10.1007/s11069-022-05430-8
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Modeling spatial landslide susceptibility in volcanic terrains through continuous neighborhood spatial analysis and multiple logistic regression in La Ciénega watershed, Nevado de Toluca, Mexico.
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- Natural Hazards, 2022, v. 113, n. 1, p. 767, doi. 10.1007/s11069-022-05323-w
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Selective ensemble deep bidirectional RVFLN for landslide displacement prediction.
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- Natural Hazards, 2022, v. 112, n. 1, p. 725, doi. 10.1007/s11069-021-05202-w
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Rainfall nowcasting model for early warning systems applied to a case over Central Italy.
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- Natural Hazards, 2022, v. 112, n. 1, p. 501, doi. 10.1007/s11069-021-05191-w
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Earthquake-induced landslide prediction using back-propagation type artificial neural network: case study in northern Iran.
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- Natural Hazards, 2022, v. 110, n. 1, p. 679, doi. 10.1007/s11069-021-04963-8
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Landslide zonation and assessment of Farizi watershed in northeastern Iran using data mining techniques.
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- Natural Hazards, 2021, v. 108, n. 3, p. 2423, doi. 10.1007/s11069-021-04805-7
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Landslide susceptibility assessment and mapping using state-of-the art machine learning techniques.
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- Natural Hazards, 2021, v. 108, n. 1, p. 1291, doi. 10.1007/s11069-021-04732-7
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Prediction of landslide displacement using multi-kernel extreme learning machine and maximum information coefficient based on variational mode decomposition: a case study in Shaanxi, China.
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- Natural Hazards, 2021, v. 108, n. 1, p. 925, doi. 10.1007/s11069-021-04713-w
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Research on displacement prediction of step-type landslide under the influence of various environmental factors based on intelligent WCA-ELM in the Three Gorges Reservoir area.
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- Natural Hazards, 2021, v. 107, n. 2, p. 1709, doi. 10.1007/s11069-021-04655-3
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A comparative analysis of attabad landslide on january 4, 2010, using two numerical models.
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- Natural Hazards, 2021, v. 107, n. 1, p. 519, doi. 10.1007/s11069-021-04593-0
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Susceptibility assessment for rainfall-induced landslides using a revised logistic regression method.
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- Natural Hazards, 2021, v. 106, n. 1, p. 97, doi. 10.1007/s11069-020-04452-4
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A novel displacement prediction method using gated recurrent unit model with time series analysis in the Erdaohe landslide.
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- Natural Hazards, 2021, v. 105, n. 1, p. 783, doi. 10.1007/s11069-020-04337-6
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Regional landslide hazard assessment through integrating susceptibility index and rainfall process.
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- Natural Hazards, 2020, v. 104, n. 3, p. 2153, doi. 10.1007/s11069-020-04265-5
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Rainfall-Induced Landslides forecast using local precipitation and global climate indexes.
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- Natural Hazards, 2020, v. 102, n. 1, p. 115, doi. 10.1007/s11069-020-03913-0
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How much does the rainfall temporal resolution affect rainfall thresholds for landslide triggering?
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- Natural Hazards, 2020, v. 100, n. 2, p. 655, doi. 10.1007/s11069-019-03830-x
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Evaluation of the effects of uncertainty on the predictions of landslide occurrences using the Shannon entropy theory and Dempster–Shafer theory.
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- Natural Hazards, 2020, v. 100, n. 1, p. 49, doi. 10.1007/s11069-019-03798-8
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Prediction on landslide displacement using a new combination model: a case study of Qinglong landslide in China.
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- Natural Hazards, 2019, v. 96, n. 3, p. 1121, doi. 10.1007/s11069-019-03595-3
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Landslide detection based on height and amplitude differences using pre- and post-event airborne X-band SAR data.
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- Natural Hazards, 2019, v. 95, n. 3, p. 485, doi. 10.1007/s11069-018-3492-8
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Landslide susceptibility assessment by Dempster-Shafer and Index of Entropy models, Sarkhoun basin, Southwestern Iran.
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- Natural Hazards, 2018, v. 93, n. 3, p. 1379, doi. 10.1007/s11069-018-3356-2
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Comparison and evaluation of landslide susceptibility maps obtained from weight of evidence, logistic regression, and artificial neural network models.
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- Natural Hazards, 2018, v. 93, n. 1, p. 249, doi. 10.1007/s11069-018-3299-7
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ShakeMap-based prediction of earthquake-induced mass movements in Switzerland calibrated on historical observations.
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- Natural Hazards, 2018, v. 92, n. 2, p. 1211, doi. 10.1007/s11069-018-3248-5
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