Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Showing 1-25 of 26 citing articles:

Interpretability of simple RNN and GRU deep learning models used to map land susceptibility to gully erosion
Hamid Gholami, Aliakbar Mohammadifar, Shahram Golzari, et al.
The Science of The Total Environment (2023) Vol. 904, pp. 166960-166960
Closed Access | Times Cited: 44
Enhancing temperature prediction in the UAE: a process-driven framework for adaptive learning with GRU-CNN hybrid models
SeyedHadi Haghrahmani
Modeling Earth Systems and Environment (2025) Vol. 11, Iss. 2
Closed Access | Times Cited: 1
Mapping of the wind erodible fraction of soil by bidirectional gated recurrent unit (BiGRU) and bidirectional recurrent neural network (BiRNN) deep learning models
Mahrooz Rezaei, Aliakbar Mohammadifar, Hamid Gholami, et al.
CATENA (2023) Vol. 223, pp. 106953-106953
Open Access | Times Cited: 28
Novel integrated modelling based on multiplicative long short-term memory (mLSTM) deep learning model and ensemble multi-criteria decision making (MCDM) models for mapping flood risk
Aliakbar Mohammadifar, Hamid Gholami, Shahram Golzari
Journal of Environmental Management (2023) Vol. 345, pp. 118838-118838
Closed Access | Times Cited: 26
Soil erodibility for water and wind erosion and its relationship to vegetation and soil properties in China's drylands
Yi Han, Wenwu Zhao, Jingyi Ding, et al.
The Science of The Total Environment (2023) Vol. 903, pp. 166639-166639
Closed Access | Times Cited: 25
Modeling land susceptibility to wind erosion hazards using LASSO regression and graph convolutional networks
Hamid Gholami, Aliakbar Mohammadifar, Kathryn E. Fitzsimmons, et al.
Frontiers in Environmental Science (2023) Vol. 11
Open Access | Times Cited: 17
A comprehensive investigation of the causes of drying and increasing saline dust in the Urmia Lake, northwest Iran, via ground and satellite observations, synoptic analysis and machine learning models
Nasim Hossein Hamzeh‎, Karim A. Shukurov, Kaveh Mohammadpour, et al.
Ecological Informatics (2023) Vol. 78, pp. 102355-102355
Closed Access | Times Cited: 16
An assessment of global land susceptibility to wind erosion based on deep-active learning modelling and interpretation techniques
Hamid Gholami, Aliakbar Mohammadifar, Yougui Song, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 7
An interpretable deep learning model to map land subsidence hazard
Paria Rahmani, Hamid Gholami, Shahram Golzari
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 11, pp. 17448-17460
Closed Access | Times Cited: 5
Explainable deep learning hybrid modeling framework for total suspended particles concentrations prediction
Sujan Ghimire, Ravinesh C. Deo, Ningbo Jiang, et al.
Atmospheric Environment (2025), pp. 121079-121079
Closed Access
Intrinsic and extrinsic techniques for quantification uncertainty of an interpretable GRU deep learning model used to predict atmospheric total suspended particulates (TSP) in Zabol, Iran during the dusty period of 120-days wind
Hamid Gholami, Aliakbar Mohammadifar, Reza Dahmardeh Behrooz, et al.
Environmental Pollution (2023) Vol. 342, pp. 123082-123082
Closed Access | Times Cited: 13
An integrated feature selection and machine learning framework for PM10 concentration prediction
Elham Kalantari, Hamid Gholami, Hossein Malakooti, et al.
Atmospheric Pollution Research (2025), pp. 102456-102456
Closed Access
Mapping of salty aeolian dust-source potential areas: Ensemble model or benchmark models?
Bahram Choubin, Farzaneh Sajedi Hosseini, Omid Rahmati, et al.
The Science of The Total Environment (2023) Vol. 877, pp. 163419-163419
Closed Access | Times Cited: 8
Variability of Middle East springtime dust events between 2011 and 2022
Parya Broomandi, David Galán‐Madruga, Alfrendo Satyanaga, et al.
Air Quality Atmosphere & Health (2024) Vol. 17, Iss. 6, pp. 1341-1360
Closed Access | Times Cited: 2
Preliminary data on artificial intelligence tool in magnetic resonance imaging assessment of degenerative pathologies of lumbar spine
Vincenza Granata, Roberta Fusco, Simone Coluccino, et al.
La radiologia medica (2024) Vol. 129, Iss. 4, pp. 623-630
Closed Access | Times Cited: 2
Dust Transport from North Africa to the Middle East: Synoptic Patterns and Numerical Forecast
Sara Karami, Dimitris G. Kaskaoutis, Ioannis Pytharoulis, et al.
Atmosphere (2024) Vol. 15, Iss. 5, pp. 531-531
Open Access | Times Cited: 2
An explainable integrated machine learning model for mapping soil erosion by wind and water in a catchment with three desiccated lakes
Hamid Gholami, Mehdi Jalali, Marzieh Rezaei, et al.
Aeolian Research (2024) Vol. 67-69, pp. 100924-100924
Closed Access | Times Cited: 2
Projection of land susceptibility to subsidence hazard in China using an interpretable CNN deep learning model
Kai Liu, Jianxin Zhang, Junfei Liu, et al.
The Science of The Total Environment (2023) Vol. 913, pp. 169502-169502
Closed Access | Times Cited: 6
Aeolian and fluvial processes influence on dust storms of Hormuz Strait and Makran coastal plains (SE Iran); insight from geomorphic landforms, and sediment texture and mineralogy
Ali Mohammadi
International Journal of Earth Sciences (2023) Vol. 112, Iss. 7, pp. 1973-1987
Closed Access | Times Cited: 5
Windblown sand hazards risk assessment along the highways based on GIS-game theory combination weight
Liangying Li, Lele LV, Zhizhong Tao, et al.
PLoS ONE (2024) Vol. 19, Iss. 2, pp. e0292263-e0292263
Open Access | Times Cited: 1
Intelligent Dust Monitoring System Based on IoT
Ali Y. Hassan, Muna Hadi Saleh
Journal of Engineering (2024) Vol. 30, Iss. 06, pp. 39-56
Open Access
Detection of land subsidence using hybrid and ensemble deep learning models
Narges Kariminejad, Aliakbar Mohammadifar, Adel Sepehr, et al.
Applied Geomatics (2024) Vol. 16, Iss. 3, pp. 593-610
Closed Access
AI-Powered Dust Storm Movement Prediction System Using Satellite Imagery
Mohamed Abdulrasool Juma Albasri, Sini Raj Pulari, Shaima Shawqi Almeer, et al.
Lecture notes in networks and systems (2024), pp. 319-329
Closed Access
High Resolution Precipitation and Soil Moisture Data Integration for Landslide Susceptibility Mapping
Yaser Peiro, Evelina Volpe, Luca Ciabatta, et al.
Geosciences (2024) Vol. 14, Iss. 12, pp. 330-330
Open Access
Combined Forecasting Method of Carbon Trading Volume Based on Wavelet Transform and CNN-GRU
浩 王
Modeling and Simulation (2023) Vol. 12, Iss. 03, pp. 2040-2048
Closed Access | Times Cited: 1
Page 1 - Next Page

Scroll to top