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Emrehan Kutluğ Şahin

Observed names: Emrehan Kutlug SAHİN, Emrehan Kutlug Sahin, Emrehan Kutluğ ŞAHİN
ORCID: 0000-0002-9830-8585
Observed ORCID: 0000-0002-9830-8585
OpenAlex ID: A5000302556
Landslide susceptibility mapping using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression
2013 · Taskin Kavzoglu, Emrehan Kutlug Sahin, et al. · Landslides · 737
Assessing the predictive capability of ensemble tree methods for landslide susceptibility mapping using XGBoost, gradient boosting machine, and random forest
2020 · Emrehan Kutlug Sahin · SN Applied Sciences · 490
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An investigation of feature selection methods for soil liquefaction prediction based on tree-based ensemble algorithms using AdaBoost, gradient boosting, and XGBoost
2022 · Selçuk Demir, Emrehan Kutlug Sahin · Neural Computing and Applications · 227
Selecting optimal conditioning factors in shallow translational landslide susceptibility mapping using genetic algorithm
2015 · Taskin Kavzoglu, Emrehan Kutlug Sahin, et al. · Engineering Geology · 214
Comparative analysis of gradient boosting algorithms for landslide susceptibility mapping
2020 · Emrehan Kutlug Sahin · Geocarto International · 208
Machine Learning Techniques in Landslide Susceptibility Mapping: A Survey and a Case Study
2018 · Taskin Kavzoglu, Ismail Colkesen, et al. · Advances in natural and technological hazards research · 186
Susceptibility mapping of shallow landslides using kernel-based Gaussian process, support vector machines and logistic regression
2016 · Ismail Colkesen, Emrehan Kutlug Sahin, et al. · Journal of African Earth Sciences · 173
A comparative assessment of canonical correlation forest, random forest, rotation forest and logistic regression methods for landslide susceptibility mapping
2018 · Emrehan Kutlug Sahin, Ismail Colkesen, et al. · Geocarto International · 158
An assessment of multivariate and bivariate approaches in landslide susceptibility mapping: a case study of Duzkoy district
2014 · Taskin Kavzoglu, Emrehan Kutlug Sahin, et al. · Natural Hazards · 155
Predicting occurrence of liquefaction-induced lateral spreading using gradient boosting algorithms integrated with particle swarm optimization: PSO-XGBoost, PSO-LightGBM, and PSO-CatBoost
2023 · Selçuk Demir, Emrehan Kutlug Sahin · Acta Geotechnica · 145
Liquefaction prediction with robust machine learning algorithms (SVM, RF, and XGBoost) supported by genetic algorithm-based feature selection and parameter optimization from the perspective of data processing
2022 · Selçuk Demir, Emrehan Kutluğ Şahin · Environmental Earth Sciences · 143
Performance analysis of advanced decision tree-based ensemble learning algorithms for landslide susceptibility mapping
2019 · Emrehan Kutlug Sahin, Ismail Colkesen · Geocarto International · 97
Comparison of tree-based machine learning algorithms for predicting liquefaction potential using canonical correlation forest, rotation forest, and random forest based on CPT data
2021 · Selcuk Demir, Emrehan Kutlug Sahin · Soil Dynamics and Earthquake Engineering · 91
Developing comprehensive geocomputation tools for landslide susceptibility mapping: LSM tool pack
2020 · Emrehan Kutlug Sahin, Ismail Colkesen, et al. · Computers & Geosciences · 79
Implementation of free and open-source semi-automatic feature engineering tool in landslide susceptibility mapping using the machine-learning algorithms RF, SVM, and XGBoost
2022 · Emrehan Kutlug Sahin · Stochastic Environmental Research and Risk Assessment · 62
Greedy-AutoML: A novel greedy-based stacking ensemble learning framework for assessing soil liquefaction potential
2022 · Emrehan Kutlug Sahin, Selcuk Demir · Engineering Applications of Artificial Intelligence · 56
The effectiveness of data pre-processing methods on the performance of machine learning techniques using RF, SVR, Cubist and SGB: a study on undrained shear strength prediction
2024 · Selçuk Demir, Emrehan Kutlug Sahin · Stochastic Environmental Research and Risk Assessment · 49
Investigation of automatic feature weighting methods (Fisher, Chi-square and Relief-F) for landslide susceptibility mapping
2016 · Emrehan Kutlug Sahin, Cengizhan Ipbuker, et al. · Geocarto International · 38
Advanced tree-based machine learning methods for predicting the seismic response of regular and irregular RC frames
2024 · Ahmet Demir, Emrehan Kutlug Sahin, et al. · Structures · 37
Application of state-of-the-art machine learning algorithms for slope stability prediction by handling outliers of the dataset
2023 · Selçuk Demir, Emrehan Kutlug Sahin · Earth Science Informatics · 35
Evaluation of Oversampling Methods (OVER, SMOTE, and ROSE) in Classifying Soil Liquefaction Dataset based on SVM, RF, and Naïve Bayes
2022 · Selçuk DEMİR, Emrehan Kutluğ ŞAHİN · European Journal of Science and Technology · 33
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An innovative machine learning approach for slope stability prediction by combining shap interpretability and stacking ensemble learning
2025 · Selçuk Demir, Emrehan Kutlug Sahin · Environmental Science and Pollution Research · 20
A Comparison of Feature and Expert-based Weighting Algorithms in Landslide Susceptibility Mapping
2015 · Emrehan Kutlug Sahin, Cengizhan Ipbuker, et al. · Procedia Earth and Planetary Science · 10
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Assessing the predictive capability of DeepBoost machine learning algorithm powered by hyperparameter tuning methods for slope stability prediction
2023 · Selçuk Demir, Emrehan Kutlug Sahin · Environmental Earth Sciences · 9
Assessment of Feature Selection for Liquefaction Prediction Based on Recursive Feature Elimination
2021 · Selçuk DEMİR, Emrehan Kutluğ ŞAHİN · European Journal of Science and Technology · 7
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Works count: 35
Citation count: 3,482
H-index: 21
I10-index: 23
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