Theo dơi
Kourosh Ahmadi
Kourosh Ahmadi
Lund University
Email được xác minh tại - Trang chủ
Tiêu đề
Trích dẫn bởi
Trích dẫn bởi
Application of support vector machine, random forest, and genetic algorithm optimized random forest models in groundwater potential mapping
SA Naghibi, K Ahmadi, A Daneshi
Water Resources Management 31, 2761-2775, 2017
Groundwater potential mapping using a novel data-mining ensemble model
MD Kordestani, SA Naghibi, H Hashemi, K Ahmadi, B Kalantar, ...
Hydrogeology journal, 2019
Landslide susceptibility mapping: Machine and ensemble learning based on remote sensing big data
B Kalantar, N Ueda, V Saeidi, K Ahmadi, AA Halin, F Shabani
Remote Sensing 12 (11), 1737, 2020
Mapping the spatial and temporal variability of flood hazard affected by climate and land-use changes in the future
S Janizadeh, SC Pal, A Saha, I Chowdhuri, K Ahmadi, S Mirzaei, ...
Journal of Environmental Management 298, 113551, 2021
Forest fire susceptibility prediction based on machine learning models with resampling algorithms on remote sensing data
B Kalantar, N Ueda, MO Idrees, S Janizadeh, K Ahmadi, F Shabani
Remote Sensing 12 (22), 3682, 2020
Non-linear height-diameter models for oriental beech (Fagus orientalis Lipsky) in the Hyrcanian forests, Iran
K Ahmadi, S Jalil Alavi, MT Kouchaksaraei, W Aertsen
Biotechnology, Agronomy, Society and Environment 17 (3), 431-440, 2013
Deep neural network utilizing remote sensing datasets for flood hazard susceptibility mapping in Brisbane, Australia
B Kalantar, N Ueda, V Saeidi, S Janizadeh, F Shabani, K Ahmadi, ...
Remote Sensing 13 (13), 2638, 2021
Comparison of machine learning methods for mapping the stand characteristics of temperate forests using multi-spectral sentinel-2 data
K Ahmadi, B Kalantar, V Saeidi, EKG Harandi, S Janizadeh, N Ueda
Remote Sensing 12 (18), 3019, 2020
The response of English yew (Taxus baccata L.) to climate change in the Caspian Hyrcanian Mixed Forest ecoregion
SJ Alavi, K Ahmadi, SM Hosseini, M Tabari, Z Nouri
Regional Environmental Change 19, 1495-1506, 2019
The current and future potential geographical distribution of Nepeta crispa Willd., an endemic, rare and threatened aromatic plant of Iran: Implications for ecological …
S Mahmoodi, M Heydari, K Ahmadi, NR Khwarahm, O Karami, ...
Ecological Indicators 137, 108752, 2022
Predicting landslide susceptibility based on decision tree machine learning models under climate and land use changes
QB Pham, S Chandra Pal, R Chakrabortty, A Saha, S Janizadeh, ...
Geocarto International 37 (25), 7881-7907, 2022
The potential impact of future climate on the distribution of European yew (Taxus baccata L.) in the Hyrcanian Forest region (Iran)
K Ahmadi, SJ Alavi, GZ Amiri, SM Hosseini, JM Serra-Diaz, JC Svenning
International Journal of Biometeorology 64, 1451-1462, 2020
Flood susceptibility modeling based on new hybrid intelligence model: Optimization of XGboost model using GA metaheuristic algorithm
NTT Linh, M Pandey, S Janizadeh, GS Bhunia, A Norouzi, S Ali, QB Pham, ...
Advances in Space Research 69 (9), 3301-3318, 2022
Assessment of groundwater potential modeling using support vector machine optimization based on Bayesian multi-objective hyperparameter algorithm
DT Anh, M Pandey, VN Mishra, KK Singh, K Ahmadi, S Janizadeh, ...
Applied Soft Computing 132, 109848, 2023
Patterns of density and structure of natural populations of Taxus baccata in the Hyrcanian forests of Iran
K Ahmadi, S Jalil Alavi, G Zahedi Amiri, S Mohsen Hosseini, ...
Nordic journal of botany 38 (3), 2020
Generalized height-diameter models for Fagus orientalis Lipsky in Hyrcanian forest, Iran.
K Ahmadi, SJ Alavi
Above-and below-ground biomass and carbon stocks of different tree plantations in central Iran
H Sohrabi, S Bakhtiarvand-Bakhtiari, K Ahmadi
Journal of Arid Land 8, 138-145, 2016
Evaluation of debris flow and landslide hazards using ensemble framework of Bayesian-and tree-based models
SC Pal, R Chakrabortty, A Saha, SK Bozchaloei, QB Pham, NTT Linh, ...
Bulletin of Engineering Geology and the Environment 81, 1-25, 2022
Constructing site quality curves and productivity assessment for uneven-aged and mixed stands of oriental beech (Fagus oriental Lipsky) in Hyrcanian forest, Iran
K Ahmadi, SJ Alavi, MT Kouchaksaraei
Forest science and technology 13 (1), 41-46, 2017
Prediction of groundwater nitrate concentration in a semiarid region using hybrid Bayesian artificial intelligence approaches
KM Alkindi, K Mukherjee, M Pandey, A Arora, S Janizadeh, QB Pham, ...
Environmental Science and Pollution Research, 1-16, 2022
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