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Flood susceptibility modeling in Teesta River basin, Bangladesh using novel ensembles of bagging algorithms

Stochastic environmental research and risk assessment, 2020-12, Vol.34 (12), p.2277-2300

2020

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A Semi-Automated Object-Based Gully Networks Detection Using Different Machine Learning Models: A Case Study of Bowen Catchment, Queensland, Australia

Sensors (Basel, Switzerland), 2019-11, Vol.19 (22), p.4893

2019

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Flood susceptibility mapping using an improved analytic network process with statistical models

Geomatics, natural hazards and risk, 2020-01, Vol.11 (1), p.2282-2314

2020

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Spatial Prediction of Future Flood Risk: An Approach to the Effects of Climate Change

Geosciences (Basel), 2021-01, Vol.11 (1), p.25

2021

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A Comparative Assessment of Random Forest and k-Nearest Neighbor Classifiers for Gully Erosion Susceptibility Mapping

Water (Basel), 2019-10, Vol.11 (10), p.2076

2019

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Interactive Changes in Climatic and Hydrological Droughts, Water Quality, and Land Use/Cover of Tajan Watershed, Northern Iran

Water (Basel), 2024-07, Vol.16 (13), p.1784

2024

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Earthquake Vulnerability Mapping Using Different Hybrid Models

Symmetry (Basel), 2020-03, Vol.12 (3), p.405

2020

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Soft Computing Ensemble Models Based on Logistic Regression for Groundwater Potential Mapping

Applied sciences, 2020-04, Vol.10 (7), p.2469

2020

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Performance Evaluation of Machine Learning Methods for Forest Fire Modeling and Prediction

Symmetry (Basel), 2020-06, Vol.12 (6), p.1022

2020

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Assessment of Ensemble Models for Groundwater Potential Modeling and Prediction in a Karst Watershed

Water (Basel), 2021-09, Vol.13 (18), p.2540

2021

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Improving Voting Feature Intervals for Spatial Prediction of Landslides

Mathematical problems in engineering, 2020, Vol.2020 (2020), p.1-15

2020

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Using machine learning models, remote sensing, and GIS to investigate the effects of changing climates and land uses on flood probability

Journal of hydrology (Amsterdam), 2021-04, Vol.595, p.125663, Article 125663

2021

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Spatial modeling of flood probability using geo-environmental variables and machine learning models, case study: Tajan watershed, Iran

Advances in space research, 2021-05, Vol.67 (10), p.3169-3186

2021

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DEM resolution effects on machine learning performance for flood probability mapping

Journal of hydro-environment research, 2022-01, Vol.40, p.1-16

2022

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Predicting temporal and spatial variability in flood vulnerability and risk of rural communities at the watershed scale

Journal of environmental management, 2022-12, Vol.323, p.116261-116261, Article 116261

2022

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Determination of flood probability and prioritization of sub-watersheds: A comparison of game theory to machine learning

Journal of environmental management, 2021-10, Vol.295, p.113040-113040, Article 113040

2021

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Optimization of statistical and machine learning hybrid models for groundwater potential mapping

Geocarto international, 2022-12, Vol.37 (13), p.3877-3911

2022

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Comprehensive assessment of resilience of flood hazard villages using a modeling and field survey approach

International journal of disaster risk reduction, 2023-10, Vol.96, p.103910, Article 103910

2023

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A novel GIS-based ensemble technique for rangeland downward trend mapping as an ecological indicator change

Ecological indicators, 2020-10, Vol.117, p.106591, Article 106591

2020

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Assessment of land degradation using machine‐learning techniques: A case of declining rangelands

Land degradation & development, 2021-02, Vol.32 (3), p.1452-1466

2021

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Prioritizing sub-watersheds based on soil-erosion potential by integrating RUSLE and game-theory algorithms

Advances in space research, 2023-07, Vol.72 (2), p.471-487

2023

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A New Approach for Smart Soil Erosion Modeling: Integration of Empirical and Machine-Learning Models

Environmental modeling & assessment, 2023-02, Vol.28 (1), p.145-160

2023

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Novel hybrid models between bivariate statistics, artificial neural networks and boosting algorithms for flood susceptibility assessment

Journal of environmental management, 2020-07, Vol.265, p.110485-110485, Article 110485

2020

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Flash-flood hazard using deep learning based on H2O R package and fuzzy-multicriteria decision-making analysis

Journal of hydrology (Amsterdam), 2022-06, Vol.609, p.127747, Article 127747

2022

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Groundwater Potential Mapping Using GIS‐Based Hybrid Artificial Intelligence Methods

Ground water, 2021-09, Vol.59 (5), p.745-760

2021

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Flood susceptibility modeling in Teesta River basin, Bangladesh using novel ensembles of bagging algorithms

A Semi-Automated Object-Based Gully Networks Detection Using Different Machine Learning Models: A Case Study of Bowen Catchment, Queensland, Australia

Flood susceptibility mapping using an improved analytic network process with statistical models

Spatial Prediction of Future Flood Risk: An Approach to the Effects of Climate Change

A Comparative Assessment of Random Forest and k-Nearest Neighbor Classifiers for Gully Erosion Susceptibility Mapping

Interactive Changes in Climatic and Hydrological Droughts, Water Quality, and Land Use/Cover of Tajan Watershed, Northern Iran

Earthquake Vulnerability Mapping Using Different Hybrid Models

Soft Computing Ensemble Models Based on Logistic Regression for Groundwater Potential Mapping

Performance Evaluation of Machine Learning Methods for Forest Fire Modeling and Prediction

Assessment of Ensemble Models for Groundwater Potential Modeling and Prediction in a Karst Watershed

Improving Voting Feature Intervals for Spatial Prediction of Landslides

Using machine learning models, remote sensing, and GIS to investigate the effects of changing climates and land uses on flood probability

Spatial modeling of flood probability using geo-environmental variables and machine learning models, case study: Tajan watershed, Iran

DEM resolution effects on machine learning performance for flood probability mapping

Predicting temporal and spatial variability in flood vulnerability and risk of rural communities at the watershed scale

Determination of flood probability and prioritization of sub-watersheds: A comparison of game theory to machine learning

Optimization of statistical and machine learning hybrid models for groundwater potential mapping

Comprehensive assessment of resilience of flood hazard villages using a modeling and field survey approach

A novel GIS-based ensemble technique for rangeland downward trend mapping as an ecological indicator change

Assessment of land degradation using machine‐learning techniques: A case of declining rangelands

Prioritizing sub-watersheds based on soil-erosion potential by integrating RUSLE and game-theory algorithms

A New Approach for Smart Soil Erosion Modeling: Integration of Empirical and Machine-Learning Models

Novel hybrid models between bivariate statistics, artificial neural networks and boosting algorithms for flood susceptibility assessment

Flash-flood hazard using deep learning based on H2O R package and fuzzy-multicriteria decision-making analysis

Groundwater Potential Mapping Using GIS‐Based Hybrid Artificial Intelligence Methods

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