F. Rezaie

发表

Technical and economic analysis of acrylonitrile production from polypropylene

V. Pirouzfar, F. Rezaie, A. Alihosseini, 2020 .

Spatial prediction of groundwater potentiality using ANFIS ensembled with teaching-learning-based and biogeography-based optimization

Wei Chen, H. Pourghasemi, M. Panahi, 2019, Journal of Hydrology.

Multi-hazard probability assessment and mapping in Iran.

H. Pourghasemi, M. Panahi, T. Blaschke, 2019, The Science of the total environment.

Spatial prediction of landslide susceptibility using hybrid support vector regression (SVR) and the adaptive neuro-fuzzy inference system (ANFIS) with various metaheuristic algorithms.

Hamid Reza Pourghasemi, Fatemeh Rezaie, Mahdi Panahi, 2020, The Science of the total environment.

Spatial prediction of groundwater potential mapping based on convolutional neural network (CNN) and support vector regression (SVR)

Hamid Reza Pourghasemi, Fatemeh Rezaie, Mahdi Panahi, 2020, Journal of Hydrology.

Hydrogen management in refineries: Retrofitting of hydrogen networks, electricity and ammonia production

A. Hamidi, R. Roshandel, F. Rezaie, 2020 .

Blue-Green Smart Mobility Technologies as Readiness for Facing Tomorrow’s Urban Shock toward the World as a Better Place for Living (Case Studies: Songdo and Copenhagen)

F. Rezaie, H. Mohammadian, Hamid Doost Mohammadian, 2020, Technologies.

Novel hybrid intelligence models for flood-susceptibility prediction: Meta optimization of the GMDH and SVR models with the genetic algorithm and harmony search

B. Pradhan, D. Bui, M. Panahi, 2020 .

Earthquake Vulnerability Assessment for Urban Areas Using an ANN and Hybrid SWOT-QSPM Model

Biswajeet Pradhan, Mohsen Alizadeh, Amin Beiranvand Pour, 2021, Remote. Sens..

Novel hybrid models by coupling support vector regression (SVR) with meta-heuristic algorithms (WOA and GWO) for flood susceptibility mapping

M. Panahi, C. Neale, F. Rezaie, 2022, Natural Hazards.

Large-scale dynamic flood monitoring in an arid-zone floodplain using SAR data and hybrid machine-learning models

M. Panahi, G. Foody, Hamid Darabi, 2022, Journal of Hydrology.

Evaluation of deep machine learning-based models of soil cumulative infiltration

K. Khosravi, S. Panahi, L. Billa, 2022, Earth Science Informatics.

Evaluation of deep machine learning-based models of soil cumulative infiltration

K. Khosravi, S. Panahi, L. Billa, 2022, Earth Science Informatics.

GIS modelling of seismic vulnerability of residential fabrics considering geotechnical , structural , social and physical distance indicators in Tehran city using multi-criteria decision-making ( MCDM ) techniques

F. Rezaie, M. Panahi, 2014 .

i-Sustainability Plus Theory as an Innovative Path towards Sustainable World Founded on Blue-Green Ubiquitous Cities (Case Studies: Denmark and South Korea)

F. Rezaie, Hamid Doost Mohammadian, 2020 .

A country-wide assessment of Iran's land subsidence susceptibility using satellite-based InSAR and machine learning

M. Panahi, K. Khosravi, A. Sharifi, 2022, Geocarto International.

Novel hybrid models by coupling support vector regression (SVR) with meta-heuristic algorithms (WOA and GWO) for flood susceptibility mapping

M. Panahi, C. Neale, F. Rezaie, 2022, Natural Hazards.

μ-Benzene-1,2,4,5-tetracarboxylato-bis[aquabis(2,2′-bipyridine)cobalt(II)] dodecahydrate

H. Khavasi, M. Ghassemzadeh, F. Rezaie, 2006 .

Spatial modeling of geogenic indoor radon distribution in Chungcheongnam-do, South Korea using enhanced machine learning algorithms.

M. Panahi, F. Rezaie, S. Bateni, 2022, Environment international.

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

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

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.

Toward the development of deep learning analyses for snow avalanche releases in mountain regions

Wei Chen, M. Panahi, Saro Lee, 2021, 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.

Compensatory growth assessment by plasma IGF-I hormone measurement and growth performance in rainbow trout (Oncorhynchus mykiss)

F. Rezaie, A. Afzali, B. M. Amiri, 2010 .

Soil water erosion susceptibility assessment using deep learning algorithms

K. Khosravi, Z. Kalantari, S. Abolfathi, 2023, Journal of Hydrology.

Debris flows modeling using geo-environmental factors: developing hybridized deep-learning algorithms

D. Bui, Wei Chen, M. Panahi, 2021, Geocarto International.

Novel cations of xenon trifluoroborazine complexes: Structures, reactivities, and natural bonding orbital analysis

S. B. A. Hamid, F. Rezaie, A. R. Oliaey, 2015 .

Meteorological data mining and hybrid data-intelligence models for reference evaporation simulation: A case study in Iraq

Zaher Mundher Yaseen, Khabat Khosravi, Binh Thai Pham, 2019, Comput. Electron. Agric..

GIS modeling of seismic vulnerability of residential fabrics considering geotechnical, structural, social and physical distance indicators in Tehran using multi-criteria decision-making techniques

Fatemeh Rezaie, Mahdi Panahi, M. Panahi, 2014 .

Meta optimization of an adaptive neuro-fuzzy inference system with grey wolf optimizer and biogeography-based optimization algorithms for spatial prediction of landslide susceptibility

Dieu Tien Bui, Binh Thai Pham, Himan Shahabi, 2019, CATENA.

Urban flood modeling using deep-learning approaches in Seoul, South Korea

Wei Chen, M. Panahi, Saro Lee, 2021 .

Convolutional neural network (CNN) with metaheuristic optimization algorithms for landslide susceptibility mapping in Icheon, South Korea.

M. Panahi, Saro Lee, K. Khosravi, 2021, Journal of environmental management.

Comparison of optimized data-driven models for landslide susceptibility mapping

A. Alesheikh, M. Panahi, F. Rezaie, 2023, Environment, Development and Sustainability.

Sustainable Innovative Project Management: Response to Improve Livability and Quality of Life：Case Studies: Iran and Germany

F. Rezaie, Mohammadian, H. Mohammadian, 2019, Inventions.

Seismic vulnerability assessment of school buildings in Tehran city based on AHP and GIS

Fatemeh Rezaie, Mahdi Panahi, M. Panahi, 2014 .

Flood spatial prediction modeling using a hybrid of meta-optimization and support vector regression modeling

Khabat Khosravi, Binh Thai Pham, Moung-Jin Lee, 2021 .

Convolutional neural network and long short-term memory algorithms for groundwater potential mapping in Anseong, South Korea

M. Panahi, F. Rezaie, Chang-Wook Lee, 2022, Journal of Hydrology: Regional Studies.

Spatial prediction of landslide susceptibility in western Serbia using hybrid support vector regression (SVR) with GWO, BAT and COA algorithms

Quoc Bao Pham, Ljubomir Gigović, Abdul-Lateef Balogun, 2021, Geoscience Frontiers.

Spatial modeling of radon potential mapping using deep learning algorithms

A. Alesheikh, M. Panahi, A. Sharifi, 2021, Geocarto International.

Application of Machine Learning Algorithms for Geogenic Radon Potential Mapping in Danyang-Gun, South Korea

Mohsen Alizadeh, Jongchun Lee, Fatemeh Rezaie, 2021, Frontiers in Environmental Science.

Radon potential mapping in Jangsu-gun, South Korea using probabilistic and deep learning algorithms.

M. Panahi, Saro Lee, F. Rezaie, 2021, Environmental pollution.

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.

SEVUCAS: A Novel GIS-Based Machine Learning Software for Seismic Vulnerability Assessment

Hamid Reza Pourghasemi, Saro Lee, Khabat Khosravi, 2019, Applied Sciences.

Big Data for Entrepreneurship Towards CSR and Sustainable Development

F. Rezaie, Hamid Doost Mohammadian, 2021, Big Data for Entrepreneurship and Sustainable Development.

Application of Statistical and Machine Learning Techniques for Habitat Potential Mapping of Siberian Roe Deer in South Korea

Saro Lee, F. Rezaie, 2021 .

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.

Spatial Prediction of Landslide Susceptibility Using GIS-Based Data Mining Techniques of ANFIS with Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO)

Yi Wang, Shaojun Li, Wei Chen, 2019, Applied Sciences.

Mapping of landslide potential in Pyeongchang-gun, South Korea, using machine learning meta-based optimization algorithms

M. Panahi, F. Rezaie, Chang-Wook Lee, 2022, The Egyptian Journal of Remote Sensing and Space Science.

Experimental wound healing using microamperage electrical stimulation in rabbits.

Mohammad Bayat, Mohammad Maroufi, M. Maroufi, 2006, Journal of rehabilitation research and development.

GIS-Based SWARA and Its Ensemble by RBF and ICA Data-Mining Techniques for Determining Suitability of Existing Schools and Site Selection of New School Buildings

Hamid Reza Pourghasemi, Mohammad Yekrangnia, Fatemeh Rezaie, 2019, Spatial Modeling in GIS and R for Earth and Environmental Sciences.

Application of the group method of data handling (GMDH) approach for landslide susceptibility zonation using readily available spatial covariates

Omid Rahmati, Fatemeh Rezaie, Mahdi Panahi, 2022, CATENA.

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

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

Development of novel optimized deep learning algorithms for wildfire modeling: A case study of Maui, Hawai'i

C. Trauernicht, M. Panahi, C. Neale, 2023, Eng. Appl. Artif. Intell..

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.

Global Review of Modification, Optimization, and Improvement Models for Aquifer Vulnerability Assessment in the Era of Climate Change

S. M. Bateni, M. Bordbar, G. Busico, 2024, Current Climate Change Reports.