A. Arabameri

发表

Spatial modelling of gully erosion using evidential belief function, logistic regression, and a new ensemble of evidential belief function–logistic regression algorithm

B. Pradhan, H. Pourghasemi, L. Lombardo, 2018, Land Degradation & Development.

GIS-based gully erosion susceptibility mapping: a comparison among three data-driven models and AHP knowledge-based technique

H. Pourghasemi, Saro Lee, A. Arabameri, 2018, Environmental Earth Sciences.

Gully erosion zonation mapping using integrated geographically weighted regression with certainty factor and random forest models in GIS.

B. Pradhan, A. Arabameri, K. Rezaei, 2019, Journal of environmental management.

Gully Head-Cut Distribution Modeling Using Machine Learning Methods—A Case Study of N.W. Iran

Thomas Blaschke, Biswajeet Pradhan, Dieu Tien Bui, 2019, Water.

An ensemble model for landslide susceptibility mapping in a forested area

Biswajeet Pradhan, Alireza Arabameri, Masoud Sohrabi, 2020, Geocarto International.

A comparison of statistical methods and multi-criteria decision making to map flood hazard susceptibility in Northern Iran.

C. Conoscenti, A. Cerda, A. Arabameri, 2019, The Science of the total environment.

Ensemble approach to develop landslide susceptibility map in landslide dominated Sikkim Himalayan region, India

A. Arabameri, Sadhan Malik, S. Pal, 2020, Environmental Earth Sciences.

A methodological comparison of head-cut based gully erosion susceptibility models: Combined use of statistical and artificial intelligence

B. Pradhan, D. Bui, L. Lombardo, 2020 .

Landslide susceptibility assessment by Dempster–Shafer and Index of Entropy models, Sarkhoun basin, Southwestern Iran

A. Arabameri, K. Shirani, M. Pasandi, 2018, Natural Hazards.

Spatial prediction of gully erosion using ALOS PALSAR data and ensemble bivariate and data mining models

B. Pradhan, A. Arabameri, K. Rezaei, 2019, Geosciences Journal.

Application of the Analytic Hierarchy Process ( AHP ) for locating fire stations : Case Study Maku City

A. Arabameri, 2014 .

Flash flood susceptibility modelling using functional tree and hybrid ensemble techniques

Biswajeet Pradhan, Dieu Tien Bui, Alireza Arabameri, 2020, Journal of Hydrology.

GIS-based landslide susceptibility mapping using numerical risk factor bivariate model and its ensemble with linear multivariate regression and boosted regression tree algorithms

Biswajeet Pradhan, Zahra Kalantari, Alireza Arabameri, 2019, Journal of Mountain Science.

Identification of erosion-prone areas using different multi-criteria decision-making techniques and GIS

Hamid Reza Pourghasemi, Biswajeet Pradhan, Alireza Arabameri, 2018 .

Prediction of landslide susceptibility in Rudraprayag, India using novel ensemble of conditional probability and boosted regression tree-based on cross-validation method.

Shahab S. Band, T. Blaschke, Viet-Ha Nhu, 2020, The Science of the total environment.

Spatial Modeling of Gully Erosion Using Linear and Quadratic Discriminant Analyses in GIS and R

Hamid Reza Pourghasemi, Alireza Arabameri, H. Pourghasemi, 2019, Spatial Modeling in GIS and R for Earth and Environmental Sciences.

GIS-based groundwater potential mapping in Shahroud plain, Iran. A comparison among statistical (bivariate and multivariate), data mining and MCDM approaches.

Alireza Arabameri, Jesús Rodrigo-Comino, Luigi Lombardo, 2019, The Science of the total environment.

Applying different scenarios for landslide spatial modeling using computational intelligence methods

Hamid Reza Pourghasemi, Alireza Arabameri, Mojtaba Yamani, 2017, Environmental Earth Sciences.

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. Bhardwaj, D. Bui, A. Arabameri, 2020, The Science of the total environment.

Comparison and evaluation of three methods of multi attribute decision making methods in choosing the best plant species for environmental management (Case study: Chah Jam Erg)

Alireza Arabameri, Mojtaba Yamani, A. Arabameri, 2015 .

Application of the novel state-of-the-art soft computing techniques for groundwater potential assessment

Muhammad Al-Amin Hoque, R. Costache, A. Cerda, 2022, Arabian Journal of Geosciences.

Predicting the deforestation probability using the binary logistic regression, random forest, ensemble rotational forest, REPTree: A case study at the Gumani River Basin, India.

A. Arabameri, Kaustuv Mukherjee, G. Paul, 2020, The Science of the total environment.

Flood susceptibility evaluation through deep learning optimizer ensembles and GIS techniques.

B. Pham, R. Costache, A. Arabameri, 2022, Journal of environmental management.

Stacking state-of-the-art ensemble for flash-flood potential assessment

R. Costache, A. Arabameri, M. Sahana, 2022, Geocarto International.

Application of AHP Model in Selection of Most Appropriate Area to Establish Soil Damp for Artificial Recharge of Underground Aquifers (Case Study: Tabas Basin)

A. Arabameri, 2015 .

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, M. Santosh, Peyman Yariyan, 2021 .

A novel ensemble computational intelligence approach for the spatial prediction of land subsidence susceptibility.

Phuong Thao Thi Ngo, B. Pradhan, A. Cerda, 2020, The Science of the total environment.

Application of the novel state-of-the-art soft computing techniques for groundwater potential assessment

Muhammad Al-Amin Hoque, R. Costache, A. Cerda, 2022, Arabian Journal of Geosciences.

Novel Ensemble of Multivariate Adaptive Regression Spline with Spatial Logistic Regression and Boosted Regression Tree for Gully Erosion Susceptibility

Biswajeet Pradhan, Saro Lee, Subodh Chandra Pal, 2020, Remote. Sens..

Flood vulnerability of a few areas in the foothills of the Western Ghats: a comparison of AHP and F-AHP models

K. S. Sajinkumar, S. L. Kuriakose, A. Rajaneesh, 2022, Stochastic Environmental Research and Risk Assessment.

Application of novel hybrid model for land subsidence susceptibility mapping

A. Arabameri, M. Santosh, Zhongjie Shen, 2022, Geological Journal.

Novel Credal Decision Tree-Based Ensemble Approaches for Predicting the Landslide Susceptibility

Saro Lee, Asish Saha, Subodh Chandra Pal, 2020, Remote. Sens..

Modeling groundwater potential using novel GIS-based machine-learning ensemble techniques

Saro Lee, A. Arabameri, H. Moayedi, 2021, Journal of Hydrology: Regional Studies.

Spatio-Temporal Assessment of Groundwater Potential Zone in the Drought-Prone Area of Bangladesh Using GIS-Based Bivariate Models

B. Pradhan, A. Arabameri, Naser Ahmed, 2021, Natural Resources Research.

Prediction of gully erosion susceptibility mapping using novel ensemble machine learning algorithms

Nhat-Duc Hoang, Romulus Costache, Biswajeet Pradhan, 2021, Geomatics, Natural Hazards and Risk.

Implementation of Artificial Intelligence Based Ensemble Models for Gully Erosion Susceptibility Assessment

Thomas Blaschke, Thomas Blaschke, Biswajeet Pradhan, 2020, Remote. Sens..

Novel Ensemble of MCDM-Artificial Intelligence Techniques for Groundwater-Potential Mapping in Arid and Semi-Arid Regions (Iran)

Saro Lee, Phuong-Thao Thi Ngo, Alireza Arabameri, 2020, Remote. Sens..

Land subsidence susceptibility assessment using advanced artificial intelligence models

R. Costache, A. Arabameri, Hairuo Yu, 2022, Geocarto International.

Flash-flood hazard susceptibility mapping in Kangsabati River Basin, India

Saro Lee, A. Arabameri, H. Moayedi, 2021, Geocarto International.

Optimization modelling to establish false measures implemented with ex-situ plant species to control gully erosion in a monsoon-dominated region with novel in-situ measurements.

A. Arabameri, S. Pal, Rabin Chakrabortty, 2021, Journal of environmental management.

Modeling Spatial Flood using Novel Ensemble Artificial Intelligence Approaches in Northern Iran

Wei Chen, Thomas Blaschke, Shahab S. Band, 2020, Remote. Sens..

Landslide Susceptibility Evaluation and Management Using Different Machine Learning Methods in The Gallicash River Watershed, Iran

Thomas Blaschke, Dieu Tien Bui, Alireza Arabameri, 2020, Remote. Sens..

Novel Machine Learning Approaches for Modelling the Gully Erosion Susceptibility

Biswajeet Pradhan, Saro Lee, Asish Saha, 2020, Remote. Sens..

Novel Ensemble Approaches of Machine Learning Techniques in Modeling the Gully Erosion Susceptibility

Biswajeet Pradhan, Phuong-Thao Thi Ngo, Alireza Arabameri, 2020, Remote. Sens..

Machine Learning-Based Gully Erosion Susceptibility Mapping: A Case Study of Eastern India

Thomas Blaschke, Dieu Tien Bui, Alireza Arabameri, 2020, Sensors.

A Novel Ensemble Approach for Landslide Susceptibility Mapping (LSM) in Darjeeling and Kalimpong Districts, West Bengal, India

Thomas Blaschke, Dieu Tien Bui, Alireza Arabameri, 2019, Remote. Sens..

Assessment of Landslide Susceptibility Using Statistical- and Artificial Intelligence-Based FR-RF Integrated Model and Multiresolution DEMs

Biswajeet Pradhan, Alireza Arabameri, Chang-Wook Lee, 2019, Remote. Sens..

Water-induced erosion potentiality and vulnerability assessment in Kangsabati river basin, eastern India

A. Arabameri, Sadhan Malik, S. Pal, 2021, Environment, Development and Sustainability.

Flash-flood hazard using Deep Learning based on H2O R package and fuzzy-multicriteria decision-making analysis

R. Costache, Binh Thai Pham, A. Arabameri, 2022, Journal of Hydrology.

Flash-flood propagation susceptibility estimation using weights of evidence and their novel ensembles with multicriteria decision making and machine learning

Sk Ajim Ali, B. Pham, R. Costache, 2021, Geocarto International.

Optimizing machine learning algorithms for spatial prediction of gully erosion susceptibility with four training scenarios

A. Arabameri, M. Santosh, O. A. Nalivan, 2023, Environmental Science and Pollution Research.

K-Fold and State-of-the-Art Metaheuristic Machine Learning Approaches for Groundwater Potential Modelling

S. Panahi, A. Arabameri, H. Moayedi, 2021, Water Resources Management.

Spatial Pattern Analysis and Prediction of Gully Erosion Using Novel Hybrid Model of Entropy-Weight of Evidence

Alireza Arabameri, Artemi Cerdà, John P. Tiefenbacher, 2019, Water.

Flash-Flood Potential Mapping Using Deep Learning, Alternating Decision Trees and Data Provided by Remote Sensing Sensors

Thomas Blaschke, Nguyen Thi Thuy Linh, Romulus Costache, 2021, Sensors.

Flood susceptibility mapping using meta-heuristic algorithms

A. Arabameri, Amir Seyed Danesh, Indrajit Chowdhuri, 2022, Geomatics, Natural Hazards and Risk.

Chemical weathering and gully erosion causing land degradation in a complex river basin of Eastern India: an integrated field, analytical and artificial intelligence approach

A. Arabameri, S. Pal, Rabin Chakrabortty, 2021, Natural Hazards.

Ensemble of Machine-Learning Methods for Predicting Gully Erosion Susceptibility

Thomas Blaschke, Asish Saha, Subodh Chandra Pal, 2020, Remote. Sens..

GIS-based statistical model for the prediction of flood hazard susceptibility

A. Arabameri, Sadhan Malik, S. Pal, 2021, Environment, Development and Sustainability.

Land-subsidence susceptibility mapping: assessment of an adaptive neuro-fuzzy inference system–genetic algorithm hybrid model

R. Costache, A. Arabameri, S. Pal, 2022, Geocarto International.

Flood Susceptibility Assessment Using Novel Ensemble of Hyperpipes and Support Vector Regression Algorithms

Thomas Blaschke, Romulus Costache, Asish Saha, 2021, Water.

Comparative assessment using boosted regression trees, binary logistic regression, frequency ratio and numerical risk factor for gully erosion susceptibility modelling

Biswajeet Pradhan, Alireza Arabameri, Luigi Lombardo, 2019 .

Have any effect of COVID-19 lockdown on environmental sustainability? A study from most polluted metropolitan area of India

A. Arabameri, S. Pal, Rabin Chakrabortty, 2021, Stochastic Environmental Research and Risk Assessment.

Weather indicators and improving air quality in association with COVID-19 pandemic in India

B. Pradhan, A. Yunus, A. Arabameri, 2021, Soft Computing.

Comparison of machine learning models for gully erosion susceptibility mapping

Biswajeet Pradhan, Dieu Tien Bui, Wei Chen, 2020, Geoscience Frontiers.

Spatial Modelling of Gully Erosion Using GIS and R Programing: A Comparison among Three Data Mining Algorithms

Hamid Reza Pourghasemi, Norman Kerle, Biswajeet Pradhan, 2018, Applied Sciences.

Performance Evaluation of GIS-Based Novel Ensemble Approaches for Land Subsidence Susceptibility Mapping

Saro Lee, A. Arabameri, H. Moayedi, 2021, Frontiers in Earth Science.

Flood vulnerability of a few areas in the foothills of the Western Ghats: a comparison of AHP and F-AHP models

K. S. Sajinkumar, S. L. Kuriakose, A. Rajaneesh, 2022, Stochastic Environmental Research and Risk Assessment.

Comparison of multi-criteria and artificial intelligence models for land-subsidence susceptibility zonation.

Phuong Thao Thi Ngo, T. Blaschke, A. Arabameri, 2021, Journal of environmental management.

Decision tree based ensemble machine learning approaches for landslide susceptibility mapping

Thomas Blaschke, Omid Ghorbanzadeh, Asish Saha, 2021, Geocarto International.

Proposing a Novel Predictive Technique for Gully Erosion Susceptibility Mapping in Arid and Semi-arid Regions (Iran)

Biswajeet Pradhan, Dieu Tien Bui, Alireza Arabameri, 2019, Remote. Sens..

Flood susceptibility mapping in Brahmaputra floodplain of Bangladesh using deep boost, deep learning neural network, and artificial neural network

A. Arabameri, Rabin Chakrabortty, Naser Ahmed, 2021, Geocarto International.

Flash-flood potential index estimation using fuzzy logic combined with deep learning neural network, naïve Bayes, XGBoost and classification and regression tree

B. Pham, R. Costache, A. Arabameri, 2021, Geocarto International.

Detection of areas prone to flood risk using state-of-the-art machine learning models

Quoc Bao Pham, Romulus Costache, Omid Ghorbanzadeh, 2021, Geomatics, Natural Hazards and Risk.

Prioritization of Flood Inundation of Maharloo Watershed in Iran Using Morphometric Parameters Analysis and TOPSIS MCDM Model

H. Pourghasemi, A. Arabameri, H. Yousefi, 2019, Spatial Modeling in GIS and R for Earth and Environmental Sciences.

Land subsidence susceptibility mapping: comparative assessment of the efficacy of the five models

A. Arabameri, S. Pal, M. Santosh, 2023, Environmental Science and Pollution Research.

Morphometric Analysis for Soil Erosion Susceptibility Mapping Using Novel GIS-Based Ensemble Model

Thomas Blaschke, Biswajeet Pradhan, Dieu Tien Bui, 2020, Remote. Sens..

Novel ensembles of COPRAS multi-criteria decision-making with logistic regression, boosted regression tree, and random forest for spatial prediction of gully erosion susceptibility.

Biswajeet Pradhan, Alireza Arabameri, Dieu Tien Bui, 2019, The Science of the total environment.

Flood Susceptibility Modeling in a Subtropical Humid Low-Relief Alluvial Plain Environment: Application of Novel Ensemble Machine Learning Approach

R. Costache, A. Arabameri, V. Mishra, 2021, Frontiers in Earth Science.

Detection of areas prone to flood-induced landslides risk using certainty factor and its hybridization with FAHP, XGBoost and deep learning neural network

Quoc Bao Pham, Romulus Costache, Duong Tran Anh, 2021 .

Drought risk assessment: integrating meteorological, hydrological, agricultural and socio-economic factors using ensemble models and geospatial techniques

Rabin Chakrabortty, Alireza Arabameri, Hossein Moayedi, 2021, Geocarto International.

Spatial modelling of gully erosion in the Ardib River Watershed using three statistical-based techniques

Biswajeet Pradhan, Dieu Tien Bui, Alireza Arabameri, 2020 .

Climate and land use change induced future flood susceptibility assessment in a sub-tropical region of India

Asish Saha, Subodh Chandra Pal, Rabin Chakrabortty, 2021, Soft Computing.

Gully erosion susceptibility mapping using GIS-based multi-criteria decision analysis techniques

Biswajeet Pradhan, Alireza Arabameri, Khalil Rezaei, 2019, CATENA.

New neural fuzzy-based machine learning ensemble for enhancing the prediction accuracy of flood susceptibility mapping

Romulus Costache, Dieu Tien Bui, Mihnea Cristian Popa, 2020 .

Hybrid Computational Intelligence Models for Improvement Gully Erosion Assessment

Thomas Blaschke, Thomas Blaschke, Dieu Tien Bui, 2020, Remote. Sens..

Spatial prediction of shallow landslide: application of novel rotational forest-based reduced error pruning tree

R. Costache, A. Arabameri, H. Moayedi, 2021, Geomatics, Natural Hazards and Risk.

Evaluation of Recent Advanced Soft Computing Techniques for Gully Erosion Susceptibility Mapping: A Comparative Study

Hamid Reza Pourghasemi, Thomas Blaschke, Biswajeet Pradhan, 2020, Sensors.

RETRACTED ARTICLE: Weather indicators and improving air quality in association with COVID-19 pandemic in India

B. Pradhan, A. Yunus, A. Arabameri, 2021, Soft Computing.

Application of novel ensemble models to improve landslide susceptibility mapping reliability

G. Scaringi, A. Arabameri, Z. Tong, 2023, Bulletin of Engineering Geology and the Environment.

Flood hazard potential evaluation using decision tree state-of-the-art models.

R. Costache, A. Arabameri, M. Sahana, 2023, Risk analysis : an official publication of the Society for Risk Analysis.

Optimization of state-ofthe-art fuzzy-metaheuristic ANFIS based machine 1 learning models for flood susceptibility prediction mapping in the Middle 2

A. Bhardwaj, D. Bui, A. Arabameri, 2020 .

Tillage Versus No-Tillage. Soil Properties and Hydrology in an Organic Persimmon Farm in Eastern Iberian Peninsula

I. Daliakopoulos, A. Kavian, A. Arabameri, 2020 .

Flash-flood susceptibility mapping: a novel credal decision tree-based ensemble approaches

A. Arabameri, M. Santosh, Aznarul Islam, 2023, Earth Science Informatics.

Application of Probabilistic and Machine Learning Models for Groundwater Potentiality Mapping in Damghan Sedimentary Plain, Iran

Omid Ghorbanzadeh, Thomas Blaschke, Dieu Tien Bui, 2019, Remote. Sens..

Modelling of piping collapses and gully headcut landforms: Evaluating topographic variables from different types of DEM

Saro Lee, A. Arabameri, S. Pal, 2021 .

Landslide susceptibility mapping: application of novel hybridization of rotation forests (RF) and Java decision trees (J48)

A. Arabameri, Amir Seyed Danesh, Hao Cui, 2023, Soft Computing.

Application of novel ensemble models and k-fold CV approaches for Land subsidence susceptibility modelling

A. Arabameri, H. Moayedi, Kaustuv Mukherjee, 2021, Stochastic Environmental Research and Risk Assessment.

Credal decision tree based novel ensemble models for spatial assessment of gully erosion and sustainable management

Majdi M. Mafarja, A. Arabameri, H. Turabieh, 2021, Scientific Reports.

Land subsidence susceptibility mapping: a new approach to improve decision stump classification (DSC) performance and combine it with four machine learning algorithms.

A. Arabameri, M. Santosh, Rui Zhao, 2024, Environmental science and pollution research international.

Zoning Mashhad Watershed for Artificial Recharge of Underground Aquifers using TOPSIS Model and GIS Technique

Alireza Arabameri, A. Arabameri, 2015 .

Spatio-temporal assessment of water quality of a tropical decaying river in India for drinking purposes and human health risk characterization

A. Arabameri, S. Pal, Md. Mofizul Hoque, 2023, Environmental Science and Pollution Research.

Application of novel ensemble models to improve landslide susceptibility mapping reliability

G. Scaringi, A. Arabameri, Z. Tong, 2023, Bulletin of Engineering Geology and the Environment.

Flood hazard potential evaluation using decision tree state-of-the-art models.

R. Costache, A. Arabameri, M. Sahana, 2023, Risk analysis : an official publication of the Society for Risk Analysis.

New Machine Learning Ensemble for Flood Susceptibility Estimation

B. Pham, R. Costache, A. Arabameri, 2022, Water Resources Management.

Earth fissure susceptibility mapping: Application of random subspace‐based novel ensemble approaches

A. Arabameri, M. Santosh, Aman Arora, 2024, Geological Journal.