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Application of convolutional neural networks featuring Bayesian optimization for landslide susceptibility assessment

Catena (Giessen), 2020-03, Vol.186, p.104249, Article 104249

2020

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Application and verification of fuzzy algebraic operators to landslide susceptibility mapping

Environmental earth sciences, 2007-04, Vol.52 (4), p.615-623

Lee, Saro

2007

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Delineation of landslide hazard areas on Penang Island, Malaysia, by using frequency ratio, logistic regression, and artificial neural network models

Environmental earth sciences, 2010-05, Vol.60 (5), p.1037-1054

2010

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Landslide susceptibility modeling based on ANFIS with teaching-learning-based optimization and Satin bowerbird optimizer

Di xue qian yuan., 2021-01, Vol.12 (1), p.93-107

2021

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Spatial flood susceptibility mapping using an explainable artificial intelligence (XAI) model

Di xue qian yuan., 2023-11, Vol.14 (6), p.101625-20, Article 101625

2023

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Application of decision tree model for the ground subsidence hazard mapping near abandoned underground coal mines

Journal of environmental management, 2013-09, Vol.127, p.166-176

2013

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Land Subsidence Susceptibility Mapping in South Korea Using Machine Learning Algorithms

Sensors (Basel, Switzerland), 2018-07, Vol.18 (8), p.2464

2018

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Landslide detection and susceptibility mapping in the Sagimakri area, Korea using KOMPSAT-1 and weight of evidence technique

Environmental earth sciences, 2013-12, Vol.70 (7), p.3197-3215

Lee, Saro

2013

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Digital Coal Geological Map

Geo Data, 2021-09, Vol.3 (3), p.1-7

Lee, Saro

2021

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Application of Ensemble-Based Machine Learning Models to Landslide Susceptibility Mapping

Remote sensing (Basel, Switzerland), 2018-08, Vol.10 (8), p.1252

2018

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Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models

Landslides, 2007-03, Vol.4 (1), p.33-41

2007

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Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran

Di xue qian yuan., 2021-03, Vol.12 (2), p.505-519

2021

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Convolutional neural network approach for spatial prediction of flood hazard at national scale of Iran

Journal of hydrology (Amsterdam), 2020-12, Vol.591, p.125552, Article 125552

2020

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Groundwater Potential Mapping Using Remote Sensing and GIS-Based Machine Learning Techniques

Remote sensing (Basel, Switzerland), 2020-04, Vol.12 (7), p.1200

2020

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Application of an evidential belief function model in landslide susceptibility mapping

Computers & geosciences, 2012-07, Vol.44, p.120-135

2012

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Flood susceptibility mapping using integrated bivariate and multivariate statistical models

Environmental earth sciences, 2014-11, Vol.72 (10), p.4001-4015

2014

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Landslide susceptibility mapping in the Damrei Romel area, Cambodia using frequency ratio and logistic regression models

Environmental earth sciences, 2006-08, Vol.50 (6), p.847-855

2006

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Spatial prediction of flood susceptibility using random-forest and boosted-tree models in Seoul metropolitan city, Korea

Geomatics, natural hazards and risk, 2017-12, Vol.8 (2), p.1185-1203

2017

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Spatial prediction of landslide susceptibility using a decision tree approach: a case study of the Pyeongchang area, Korea

International journal of remote sensing, 2014-01, Vol.35 (16), p.6089-6112

2014

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Landslide Susceptibility Mapping and Comparison Using Decision Tree Models: A Case Study of Jumunjin Area, Korea

Remote sensing (Basel, Switzerland), 2018-10, Vol.10 (10), p.1545

2018

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GIS mapping of regional probabilistic groundwater potential in the area of Pohang City, Korea

Journal of hydrology (Amsterdam), 2011-03, Vol.399 (3), p.158-172

2011

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Combining landslide susceptibility maps obtained from frequency ratio, logistic regression, and artificial neural network models using ASTER images and GIS

Engineering geology, 2012-01, Vol.124, p.12-23

2012

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Remote Sensing and Geoscience Information Systems Applied to Groundwater Research

Remote sensing (Basel, Switzerland), 2021-06, Vol.13 (11), p.2086

2021

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Social Vulnerability Assessment Using Artificial Neural Network (ANN) Model for Earthquake Hazard in Tabriz City, Iran

Sustainability, 2018-09, Vol.10 (10), p.3376

2018

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Ensemble of Machine-Learning Methods for Predicting Gully Erosion Susceptibility

Remote sensing (Basel, Switzerland), 2020-11, Vol.12 (22), p.3675

2020

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Application of convolutional neural networks featuring Bayesian optimization for landslide susceptibility assessment

Application and verification of fuzzy algebraic operators to landslide susceptibility mapping

Delineation of landslide hazard areas on Penang Island, Malaysia, by using frequency ratio, logistic regression, and artificial neural network models

Landslide susceptibility modeling based on ANFIS with teaching-learning-based optimization and Satin bowerbird optimizer

Spatial flood susceptibility mapping using an explainable artificial intelligence (XAI) model

Application of decision tree model for the ground subsidence hazard mapping near abandoned underground coal mines

Land Subsidence Susceptibility Mapping in South Korea Using Machine Learning Algorithms

Landslide detection and susceptibility mapping in the Sagimakri area, Korea using KOMPSAT-1 and weight of evidence technique

Digital Coal Geological Map

Application of Ensemble-Based Machine Learning Models to Landslide Susceptibility Mapping

Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models

Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran

Convolutional neural network approach for spatial prediction of flood hazard at national scale of Iran

Groundwater Potential Mapping Using Remote Sensing and GIS-Based Machine Learning Techniques

Application of an evidential belief function model in landslide susceptibility mapping

Flood susceptibility mapping using integrated bivariate and multivariate statistical models

Landslide susceptibility mapping in the Damrei Romel area, Cambodia using frequency ratio and logistic regression models

Spatial prediction of flood susceptibility using random-forest and boosted-tree models in Seoul metropolitan city, Korea

Spatial prediction of landslide susceptibility using a decision tree approach: a case study of the Pyeongchang area, Korea

Landslide Susceptibility Mapping and Comparison Using Decision Tree Models: A Case Study of Jumunjin Area, Korea

GIS mapping of regional probabilistic groundwater potential in the area of Pohang City, Korea

Combining landslide susceptibility maps obtained from frequency ratio, logistic regression, and artificial neural network models using ASTER images and GIS

Remote Sensing and Geoscience Information Systems Applied to Groundwater Research

Social Vulnerability Assessment Using Artificial Neural Network (ANN) Model for Earthquake Hazard in Tabriz City, Iran

Ensemble of Machine-Learning Methods for Predicting Gully Erosion Susceptibility

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