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Alireza Arabameri
Alireza Arabameri
Department of Geomorphology, Tarbiat Modares University
Bestätigte E-Mail-Adresse bei modares.ac.ir
Titel
Zitiert von
Zitiert von
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Erodibility prioritization of sub-watersheds using morphometric parameters analysis and its mapping: A comparison among TOPSIS, VIKOR, SAW, and CF multi-criteria decision …
AA Ameri, HR Pourghasemi, A Cerda
Science of the Total Environment 613, 1385-1400, 2018
1852018
A comparison of statistical methods and multi-criteria decision making to map flood hazard susceptibility in Northern Iran
A Arabameri, K Rezaei, A Cerdà, C Conoscenti, Z Kalantari
Science of the Total Environment 660, 443-458, 2019
1822019
GIS-based groundwater potential mapping in Shahroud plain, Iran. A comparison among statistical (bivariate and multivariate), data mining and MCDM approaches
A Arabameri, K Rezaei, A Cerda, L Lombardo, J Rodrigo-Comino
Science of the total environment 658, 160-177, 2019
1462019
GIS-based gully erosion susceptibility mapping: a comparison among three data-driven models and AHP knowledge-based technique
A Arabameri, K Rezaei, HR Pourghasemi, S Lee, M Yamani
Environmental earth sciences 77, 1-22, 2018
1292018
Gully erosion zonation mapping using integrated geographically weighted regression with certainty factor and random forest models in GIS
A Arabameri, B Pradhan, K Rezaei
Journal of environmental management 232, 928-942, 2019
1232019
A novel ensemble approach for landslide susceptibility mapping (LSM) in Darjeeling and Kalimpong districts, West Bengal, India
J Roy, S Saha, A Arabameri, T Blaschke, DT Bui
Remote Sensing 11 (23), 2866, 2019
1132019
GIS-based landslide susceptibility mapping using numerical risk factor bivariate model and its ensemble with linear multivariate regression and boosted regression tree algorithms
A Arabameri, B Pradhan, K Rezaei, M Sohrabi, Z Kalantari
Journal of Mountain Science 16 (3), 595-618, 2019
1132019
Optimization of state-of-the-art fuzzy-metaheuristic ANFIS-based machine learning models for flood susceptibility prediction mapping in the Middle Ganga Plain, India
A Arora, A Arabameri, M Pandey, MA Siddiqui, UK Shukla, DT Bui, ...
Science of the Total Environment 750, 141565, 2021
1102021
Landslide susceptibility evaluation and management using different machine learning methods in the Gallicash River Watershed, Iran
A Arabameri, S Saha, J Roy, W Chen, T Blaschke, D Tien Bui
Remote Sensing 12 (3), 475, 2020
1102020
Spatial modelling of gully erosion using GIS and R programing: A comparison among three data mining algorithms
A Arabameri, B Pradhan, HR Pourghasemi, K Rezaei, N Kerle
Applied sciences 8 (8), 1369, 2018
1102018
Comparison of machine learning models for gully erosion susceptibility mapping
A Arabameri, W Chen, M Loche, X Zhao, Y Li, L Lombardo, A Cerda, ...
Geoscience Frontiers 11 (5), 1609-1620, 2020
982020
Gully erosion susceptibility mapping using GIS-based multi-criteria decision analysis techniques
A Arabameri, B Pradhan, K Rezaei, C Conoscenti
Catena 180, 282-297, 2019
932019
Spatial modelling of gully erosion using evidential belief function, logistic regression, and a new ensemble of evidential belief function–logistic regression algorithm
A Arabameri, B Pradhan, K Rezaei, M Yamani, HR Pourghasemi, ...
Land Degradation & Development 29 (11), 4035-4049, 2018
922018
Assessment of landslide susceptibility using statistical-and artificial intelligence-based FR–RF integrated model and multiresolution DEMs
A Arabameri, B Pradhan, K Rezaei, CW Lee
Remote Sensing 11 (9), 999, 2019
912019
Flood susceptibility assessment using novel ensemble of hyperpipes and support vector regression algorithms
A Saha, SC Pal, A Arabameri, T Blaschke, S Panahi, I Chowdhuri, ...
Water 13 (2), 241, 2021
892021
Novel ensembles of COPRAS multi-criteria decision-making with logistic regression, boosted regression tree, and random forest for spatial prediction of gully erosion susceptibility
A Arabameri, M Yamani, B Pradhan, A Melesse, K Shirani, DT Bui
Science of the total environment 688, 903-916, 2019
852019
Predicting the deforestation probability using the binary logistic regression, random forest, ensemble rotational forest, REPTree: A case study at the Gumani River Basin, India
S Saha, M Saha, K Mukherjee, A Arabameri, PTT Ngo, GC Paul
Science of the Total Environment 730, 139197, 2020
802020
Identification of erosion-prone areas using different multi-criteria decision-making techniques and GIS
A Arabameri, B Pradhan, HR Pourghasemi, K Rezaei
Geomatics, Natural Hazards and Risk 9 (1), 1129-1155, 2018
772018
Comparative assessment using boosted regression trees, binary logistic regression, frequency ratio and numerical risk factor for gully erosion susceptibility modelling
A Arabameri, B Pradhan, L Lombardo
Catena 183, 104223, 2019
762019
Flash flood susceptibility modelling using functional tree and hybrid ensemble techniques
A Arabameri, S Saha, W Chen, J Roy, B Pradhan, DT Bui
Journal of Hydrology 587, 125007, 2020
722020
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