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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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Contrasting effects of monochromatic LED lighting on growth, pigments and photosynthesis in the commercially important cyanobacterium Arthrospira maxima

Bioresource technology, 2019-11, Vol.291, p.121846-121846, Article 121846

2019

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Prediction of the Strength of Rubberized Concrete by an Evolved Random Forest Model

Advances in civil engineering, 2019, Vol.2019 (1)

2019

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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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Application of artificial neural networks for predicting tree survival and mortality in the Hyrcanian forest of Iran

Computers and electronics in agriculture, 2019-09, Vol.164, p.104929, Article 104929

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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A novel hybrid artificial intelligence approach for flood susceptibility assessment

Environmental modelling & software : with environment data news, 2017-09, Vol.95, p.229-245

2017

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Landslide Susceptibility Assessment Using Bagging Ensemble Based Alternating Decision Trees, Logistic Regression and J48 Decision Trees Methods: A Comparative Study

Geotechnical and geological engineering, 2017-12, Vol.35 (6), p.2597-2611

2017

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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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Evaluating scale effects of topographic variables in landslide susceptibility models using GIS-based machine learning techniques

Scientific reports, 2019-08, Vol.9 (1), p.12296-21, Article 12296

2019

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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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A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran

The Science of the total environment, 2018-06, Vol.627, p.744-755

2018

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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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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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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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Different sampling strategies for predicting landslide susceptibilities are deemed less consequential with deep learning

The Science of the total environment, 2020-06, Vol.720, p.137320-137320, Article 137320

2020

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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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Novel GIS Based Machine Learning Algorithms for Shallow Landslide Susceptibility Mapping

Sensors (Basel, Switzerland), 2018-11, Vol.18 (11), p.3777

2018

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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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Flash flood susceptibility modeling using an optimized fuzzy rule based feature selection technique and tree based ensemble methods

The Science of the total environment, 2019-06, Vol.668, p.1038-1054

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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Next-generation gene drive for population modification of the malaria vector mosquito, Anopheles gambiae

Proceedings of the National Academy of Sciences - PNAS, 2020-09, Vol.117 (37), p.22805-22814

2020

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Bifunctional and binder-free S-doped Ni-P nanospheres electrocatalyst fabricated by pulse electrochemical deposition method for overall water splitting

Journal of colloid and interface science, 2020-10, Vol.577, p.265-278

2020

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

Contrasting effects of monochromatic LED lighting on growth, pigments and photosynthesis in the commercially important cyanobacterium Arthrospira maxima

Prediction of the Strength of Rubberized Concrete by an Evolved Random Forest Model

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

Application of artificial neural networks for predicting tree survival and mortality in the Hyrcanian forest of Iran

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

A novel hybrid artificial intelligence approach for flood susceptibility assessment

Landslide Susceptibility Assessment Using Bagging Ensemble Based Alternating Decision Trees, Logistic Regression and J48 Decision Trees Methods: A Comparative Study

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

Evaluating scale effects of topographic variables in landslide susceptibility models using GIS-based machine learning techniques

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

A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran

Bagging based Support Vector Machines for spatial prediction of landslides

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

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

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

Different sampling strategies for predicting landslide susceptibilities are deemed less consequential with deep learning

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

Novel GIS Based Machine Learning Algorithms for Shallow Landslide Susceptibility Mapping

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

Flash flood susceptibility modeling using an optimized fuzzy rule based feature selection technique and tree based ensemble methods

Shallow landslide susceptibility assessment using a novel hybrid intelligence approach

Next-generation gene drive for population modification of the malaria vector mosquito, Anopheles gambiae

Bifunctional and binder-free S-doped Ni-P nanospheres electrocatalyst fabricated by pulse electrochemical deposition method for overall water splitting

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