Theo dơi
Peyman Yariyan
Peyman Yariyan
PhD candidate in RS/GIS, University of Tabriz
Email được xác minh tại - Trang chủ
Tiêu đề
Trích dẫn bởi
Trích dẫn bởi
Improvement of best first decision trees using bagging and dagging ensembles for flood probability mapping
P Yariyan, S Janizadeh, T Van Phong, HD Nguyen, R Costache, ...
Water Resources Management 34, 3037-3053, 2020
Earthquake risk assessment using an integrated Fuzzy Analytic Hierarchy Process with Artificial Neural Networks based on GIS: A case study of Sanandaj in Iran
P Yariyan, H Zabihi, ID Wolf, M Karami, S Amiriyan
International Journal of Disaster Risk Reduction 50, 101705, 2020
Flood susceptibility mapping using an improved analytic network process with statistical models
P Yariyan, M Avand, RA Abbaspour, A Torabi Haghighi, R Costache, ...
Geomatics, Natural Hazards and Risk 11 (1), 2282-2314, 2020
GIS-based spatial modeling of snow avalanches using four novel ensemble models
P Yariyan, M Avand, RA Abbaspour, M Karami, JP Tiefenbacher
Science of The Total Environment 745, 141008, 2020
Earthquake vulnerability mapping using different hybrid models
P Yariyan, M Avand, F Soltani, O Ghorbanzadeh, T Blaschke
Symmetry 12 (3), 405, 2020
A new modeling approach for spatial prediction of flash flood with biogeography optimized CHAID tree ensemble and remote sensing data
VN Nguyen, P Yariyan, M Amiri, A Dang Tran, TD Pham, MP Do, ...
Remote Sensing 12 (9), 1373, 2020
Optimization of Statistical and Machines Learning Hybrid Models for Groundwater Potential Mapping
P Yariyan, M Avand, E Omidvar, QB Pham, NTT Linh, JP Tiefenbacher
Geocarto International, 1-34, 2021
A novel GIS-based ensemble technique for rangeland downward trend mapping as an ecological indicator change
S Yousefi, M Avand, P Yariyan, HR Pourghasemi, S Keesstra, S Tavangar, ...
Ecological Indicators 117, 106591, 2020
Identification of the most suitable afforestation sites by Juniperus excels specie using machine learning models: Firuzkuh semi-arid region, Iran
S Yousefi, M Avand, P Yariyan, HJ Goujani, R Costache, S Tavangar, ...
Ecological Informatics 65, 101427, 2021
Assessment of Gini-, entropy-and ratio-based classification trees for groundwater potential modelling and prediction
O Rahmati, M Avand, P Yariyan, JP Tiefenbacher, A Azareh, DT Bui
Geocarto International 37 (12), 3397-3415, 2022
Evaluating the application of K-mean clustering in Earthquake vulnerability mapping of Istanbul, Turkey
M Shafapourtehrany, P Yariyan, H Özener, B Pradhan, F Shabani
International Journal of Disaster Risk Reduction 79, 103154, 2022
Exploitation of MCDA to Learn the Radial Base Neural Network (RBFNN) aim physical and social vulnerability analysis versus the earthquake (case study: Sanandaj City, Iran)
P Yariyan, MR Karami, R Ali Abbaspour
The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2019
GIS-based seismic vulnerability mapping: a comparison of artificial neural networks hybrid models
P Yariyan, R Ali Abbaspour, A Chehreghan, MR Karami, A Cerda
Geocarto International 37 (15), 4312-4335, 2022
Spatial modeling of radon potential mapping using deep learning algorithms
M Panahi, P Yariyan, F Rezaie, SW Kim, A Sharifi, AA Alesheikh, J Lee, ...
Geocarto International 37 (25), 9560-9582, 2022
An optimization on machine learning algorithms for mapping snow avalanche susceptibility
P Yariyan, E Omidvar, F Minaei, R Ali Abbaspour, JP Tiefenbacher
Natural Hazards, 1-36, 2022
Land subsidence spatial modeling and assessment of the contribution of geo-environmental factors to land subsidence: comparison of different novel ensemble modeling approaches
A Arabameri, P Yariyan, M Santosh
Earthquake vulnerability mapping using different hybrid models. Symmetry 12 (3): 405
P Yariyan, M Avand, F Soltani, O Ghorbanzadeh, T Blaschke
Evaluating novel hybrid models based on GIS for snow avalanche susceptibility mapping: A comparative study
P Yariyan, E Omidvar, M Karami, A Cerdà, QB Pham, JP Tiefenbacher
Cold Regions Science and Technology 194, 103453, 2022
Spatial analysis of environmental factors influencing dust sources in the east of Iran using a new active-learning approach
P Yariyan, M Amiri, M Saffariha, M Avand, SS Ghiasi, JP Tiefenbacher
Geocarto International 37 (26), 11929-11954, 2022
Assessment and uncertainty urban vulnerability caused by earthquake using FAHP model (Case study: Sanandaj)
P Yariyan, M Karami
Journal of Geography and Environmental Hazards 8 (3), 203-185, 2019
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