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Seyed Vahid Razavi-Termeh
Seyed Vahid Razavi-Termeh
Ph.D. in GIS
Verified email at mail.kntu.ac.ir
Title
Cited by
Cited by
Year
Flood susceptibility mapping using novel ensembles of adaptive neuro fuzzy inference system and metaheuristic algorithms
SVR Termeh, A Kornejady, HR Pourghasemi, S Keesstra
Science of the Total Environment 615, 438-451, 2018
4122018
Optimization of an adaptive neuro-fuzzy inference system for groundwater potential mapping
TSV Razavi, K Khabat, S Majid, SD Keesstra, FTC Tsai, D Roel, BT Pham
Hydrogeology Journal 27 (7), 2511-2534, 2019
972019
Genetic and firefly metaheuristic algorithms for an optimized neuro-fuzzy prediction modeling of wildfire probability
A Jaafari, SVR Termeh, DT Bui
Journal of environmental management 243, 358-369, 2019
852019
Groundwater potential mapping using an integrated ensemble of three bivariate statistical models with random forest and logistic model tree models
SV Razavi-Termeh, A Sadeghi-Niaraki, SM Choi
Water 11 (8), 1596, 2019
722019
An assessment of metaheuristic approaches for flood assessment
HR Pourghasemi, SV Razavi-Termeh, N Kariminejad, H Hong, W Chen
Journal of Hydrology 582, 124536, 2020
642020
Ubiquitous GIS-based forest fire susceptibility mapping using artificial intelligence methods
SV Razavi-Termeh, A Sadeghi-Niaraki, SM Choi
Remote Sensing 12 (10), 1689, 2020
582020
Spatio-temporal modeling of PM2. 5 risk mapping using three machine learning algorithms
SZ Shogrkhodaei, SV Razavi-Termeh, A Fathnia
Environmental Pollution 289, 117859, 2021
532021
Land subsidence susceptibility mapping using persistent scatterer SAR interferometry technique and optimized hybrid machine learning algorithms
B Ranjgar, SV Razavi-Termeh, F Foroughnia, A Sadeghi-Niaraki, ...
Remote Sensing 13 (7), 1326, 2021
482021
Gully erosion susceptibility mapping using artificial intelligence and statistical models
SV Razavi-Termeh, A Sadeghi-Niaraki, SM Choi
Geomatics, Natural Hazards and Risk 11 (1), 821-844, 2020
442020
Mapping of landslide susceptibility using the combination of neuro-fuzzy inference system (ANFIS), ant colony (ANFIS-ACOR), and differential evolution (ANFIS-DE) models
SV Razavi-Termeh, K Shirani, M Pasandi
Bulletin of Engineering Geology and the Environment 80, 2045-2067, 2021
372021
Asthma-prone areas modeling using a machine learning model
SV Razavi-Termeh, A Sadeghi-Niaraki, SM Choi
Scientific Reports 11 (1), 1912, 2021
372021
Improving groundwater potential mapping using metaheuristic approaches
SV Razavi-Termeh, K Khosravi, A Sadeghi-Niaraki, SM Choi, VP Singh
Hydrological Sciences Journal 65 (16), 2729-2749, 2020
342020
Flood susceptibility mapping using multi-temporal SAR imagery and novel integration of nature-inspired algorithms into support vector regression
S Mehravar, SV Razavi-Termeh, A Moghimi, B Ranjgar, F Foroughnia, ...
Journal of Hydrology 617, 129100, 2023
292023
Effects of air pollution in spatio-temporal modeling of asthma-prone areas using a machine learning model
SV Razavi-Termeh, A Sadeghi-Niaraki, SM Choi
Environmental Research 200, 111344, 2021
292021
Spatial modelling of accidents risk caused by driver drowsiness with data mining algorithms
F Farhangi, A Sadeghi-Niaraki, A Nahvi, SV Razavi-Termeh
Geocarto International 37 (9), 2698-2716, 2022
252022
Landslide susceptibility assessment in the Anfu County, China: comparing different statistical and probabilistic models considering the new topo-hydrological factor (HAND)
H Hong, A Kornejady, A Soltani, SVR Termeh, J Liu, AX Zhu, AY Hesar, ...
Earth Science Informatics 11, 605-622, 2018
252018
Covid-19 risk mapping with considering socio-economic criteria using machine learning algorithms
SV Razavi-Termeh, A Sadeghi-Niaraki, F Farhangi, SM Choi
International journal of environmental research and public health 18 (18), 9657, 2021
202021
Evaluation of tree-based machine learning algorithms for accident risk mapping caused by driver lack of alertness at a national scale
F Farhangi, A Sadeghi-Niaraki, SV Razavi-Termeh, SM Choi
Sustainability 13 (18), 10239, 2021
202021
Spatial modeling of asthma-prone areas using remote sensing and ensemble machine learning algorithms
SV Razavi-Termeh, A Sadeghi-Niaraki, SM Choi
Remote Sensing 13 (16), 3222, 2021
202021
A spatially based machine learning algorithm for potential mapping of the hearing senses in an urban environment
M Farahani, SV Razavi-Termeh, A Sadeghi-Niaraki
Sustainable Cities and Society 80, 103675, 2022
172022
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