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GIS-based modeling of rainfall-induced landslides using data mining-based functional trees classifier with AdaBoost, Bagging, and MultiBoost ensemble frameworks

Environmental earth sciences, 2016-07, Vol.75 (14), p.1, Article 1101

2016

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Flood Spatial Modeling in Northern Iran Using Remote Sensing and GIS: A Comparison between Evidential Belief Functions and Its Ensemble with a Multivariate Logistic Regression Model

Remote sensing (Basel, Switzerland), 2019-07, Vol.11 (13), p.1589

2019

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Wildfire Probability Mapping: Bivariate vs. Multivariate Statistics

Remote sensing (Basel, Switzerland), 2019-03, Vol.11 (6), p.618

2019

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Using GIS, Remote Sensing, and Machine Learning to Highlight the Correlation between the Land-Use/Land-Cover Changes and Flash-Flood Potential

Remote sensing (Basel, Switzerland), 2020-05, Vol.12 (9), p.1422

2020

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Spatial prediction of landslides using a hybrid machine learning approach based on Random Subspace and Classification and Regression Trees

Geomorphology (Amsterdam, Netherlands), 2018-02, Vol.303, p.256-270

2018

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A novel hybrid intelligent model of support vector machines and the MultiBoost ensemble for landslide susceptibility modeling

Bulletin of engineering geology and the environment, 2019-06, Vol.78 (4), p.2865-2886

2019

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Prediction of ground vibration induced by blasting operations through the use of the Bayesian Network and random forest models

Soil dynamics and earthquake engineering (1984), 2020-12, Vol.139, p.106390, Article 106390

2020

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Hybrid integration of Multilayer Perceptron Neural Networks and machine learning ensembles for landslide susceptibility assessment at Himalayan area (India) using GIS

Catena (Giessen), 2017-02, Vol.149, p.52-63

2017

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Meta optimization of an adaptive neuro-fuzzy inference system with grey wolf optimizer and biogeography-based optimization algorithms for spatial prediction of landslide susceptibility

Catena (Giessen), 2019-04, Vol.175, p.430-445

2019

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Bagging based Support Vector Machines for spatial prediction of landslides

Environmental earth sciences, 2018-02, Vol.77 (4), Article 146

2018

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A novel hybrid model of Bagging-based Naïve Bayes Trees for landslide susceptibility assessment

Bulletin of engineering geology and the environment, 2019-04, Vol.78 (3), p.1911-1925

2019

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Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)

Catena (Giessen), 2018-04, Vol.163, p.399-413

2018

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Bedload transport rate prediction: Application of novel hybrid data mining techniques

Journal of hydrology (Amsterdam), 2020-06, Vol.585, p.124774, Article 124774

2020

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Evaluation and comparison of LogitBoost Ensemble, Fisher's Linear Discriminant Analysis, logistic regression and support vector machines methods for landslide susceptibility mapping

Geocarto international, 2019-02, Vol.34 (3), p.316-333

2019

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A comparative assessment of flood susceptibility modeling using Multi-Criteria Decision-Making Analysis and Machine Learning Methods

Journal of hydrology (Amsterdam), 2019-06, Vol.573, p.311-323

2019

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Shallow landslide susceptibility assessment using a novel hybrid intelligence approach

Environmental earth sciences, 2017, Vol.76 (2), p.1-18, Article 60

2017

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Hybrid computational intelligence models for groundwater potential mapping

Catena (Giessen), 2019-11, Vol.182, p.104101, Article 104101

2019

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Landslide susceptibility modeling using Reduced Error Pruning Trees and different ensemble techniques: Hybrid machine learning approaches

Catena (Giessen), 2019-04, Vol.175, p.203-218

2019

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A Novel Classifier Based on Composite Hyper-cubes on Iterated Random Projections for Assessment of Landslide Susceptibility

Journal of the Geological Society of India, 2018-03, Vol.91 (3), p.355-362

Pham, Binh Thai

2018

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Soil erosion potential hotspot zone identification using machine learning and statistical approaches in eastern India

Natural hazards (Dordrecht), 2020-11, Vol.104 (2), p.1259-1294

2020

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Flood spatial prediction modeling using a hybrid of meta-optimization and support vector regression modeling

Catena (Giessen), 2021-04, Vol.199, p.105114, Article 105114

2021

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A novel artificial intelligence approach based on Multi-layer Perceptron Neural Network and Biogeography-based Optimization for predicting coefficient of consolidation of soil

Catena (Giessen), 2019-02, Vol.173, p.302-311

2019

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Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous watershed, Japan

Landslides, 2020-03, Vol.17 (3), p.641-658

2020

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Flood risk assessment using hybrid artificial intelligence models integrated with multi-criteria decision analysis in Quang Nam Province, Vietnam

Journal of hydrology (Amsterdam), 2021-01, Vol.592, p.125815, Article 125815

2021

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Coupling RBF neural network with ensemble learning techniques for landslide susceptibility mapping

Catena (Giessen), 2020-12, Vol.195, p.104805, Article 104805

2020

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GIS-based modeling of rainfall-induced landslides using data mining-based functional trees classifier with AdaBoost, Bagging, and MultiBoost ensemble frameworks

Flood Spatial Modeling in Northern Iran Using Remote Sensing and GIS: A Comparison between Evidential Belief Functions and Its Ensemble with a Multivariate Logistic Regression Model

Wildfire Probability Mapping: Bivariate vs. Multivariate Statistics

Using GIS, Remote Sensing, and Machine Learning to Highlight the Correlation between the Land-Use/Land-Cover Changes and Flash-Flood Potential

Spatial prediction of landslides using a hybrid machine learning approach based on Random Subspace and Classification and Regression Trees

A novel hybrid intelligent model of support vector machines and the MultiBoost ensemble for landslide susceptibility modeling

Prediction of ground vibration induced by blasting operations through the use of the Bayesian Network and random forest models

Hybrid integration of Multilayer Perceptron Neural Networks and machine learning ensembles for landslide susceptibility assessment at Himalayan area (India) using GIS

Meta optimization of an adaptive neuro-fuzzy inference system with grey wolf optimizer and biogeography-based optimization algorithms for spatial prediction of landslide susceptibility

Bagging based Support Vector Machines for spatial prediction of landslides

A novel hybrid model of Bagging-based Naïve Bayes Trees for landslide susceptibility assessment

Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)

Bedload transport rate prediction: Application of novel hybrid data mining techniques

Evaluation and comparison of LogitBoost Ensemble, Fisher's Linear Discriminant Analysis, logistic regression and support vector machines methods for landslide susceptibility mapping

A comparative assessment of flood susceptibility modeling using Multi-Criteria Decision-Making Analysis and Machine Learning Methods

Shallow landslide susceptibility assessment using a novel hybrid intelligence approach

Hybrid computational intelligence models for groundwater potential mapping

Landslide susceptibility modeling using Reduced Error Pruning Trees and different ensemble techniques: Hybrid machine learning approaches

A Novel Classifier Based on Composite Hyper-cubes on Iterated Random Projections for Assessment of Landslide Susceptibility

Soil erosion potential hotspot zone identification using machine learning and statistical approaches in eastern India

Flood spatial prediction modeling using a hybrid of meta-optimization and support vector regression modeling

A novel artificial intelligence approach based on Multi-layer Perceptron Neural Network and Biogeography-based Optimization for predicting coefficient of consolidation of soil

Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous watershed, Japan

Flood risk assessment using hybrid artificial intelligence models integrated with multi-criteria decision analysis in Quang Nam Province, Vietnam

Coupling RBF neural network with ensemble learning techniques for landslide susceptibility mapping

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