سامانه مدیریت امور پژوهشی دانشگاه کردستان | چان ج کلاگیو

نام و نام خانوادگی	چان ج کلاگیو
شغل	پژوهشگر خارجی
تحصیلات	دکترای تخصصی
وبسایت
پست الکترونیک	—

	عنوان	مجله
1	Performance improvement of the linear muskingum flood routing model using optimization algorithms and data assimilation approaches	Natural Hazards
2	Rangeland species potential mapping using machine learning algorithms	ECOLOGICAL ENGINEERING
3	Towards robust smart data-driven soil erodibility index prediction under different scenarios	Geocarto International
4	Can deep learning algorithms outperform benchmark machine learning algorithms in flood susceptibility modeling?	JOURNAL OF HYDROLOGY
5	Flash flood susceptibility mapping using a novel deep learning model based on deep belief network, back propagation and genetic algorithm	Geoscience Frontiers
6	A novel ensemble learning based on Bayesian Belief Network coupled with an extreme learning machine for flash flood susceptibility mapping	Engineering Applications of Artificial Intelligence
7	New Ensemble Models for Shallow Landslide Susceptibility Modeling in a Semi-Arid Watershed	FORESTS
8	Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms	International Journal of Environmental Research and Public Health
9	Landslide Susceptibility Mapping Using Machine Learning Algorithms and Remote Sensing Data in a Tropical Environment	International Journal of Environmental Research and Public Health
10	Shallow Landslide Susceptibility Mapping by Random Forest Base Classifier and Its Ensembles in a Semi-Arid Region of Iran	FORESTS
11	GIS-Based Gully Erosion Susceptibility Mapping: A Comparison of Computational Ensemble Data Mining Models	Applied Sciences-Basel
12	Flood Detection and Susceptibility Mapping Using Sentinel-1 Remote Sensing Data and a Machine Learning Approach: Hybrid Intelligence of Bagging Ensemble Based on K-Nearest Neighbor Classifier	Remote Sensing
13	Shallow Landslide Prediction Using a Novel Hybrid Functional Machine Learning Algorithm	Remote Sensing