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OpenAlex Citation Counts

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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:

Earth fissure hazard prediction using machine learning models
Bahram Choubin, Amir Mosavi, Esmail Heydari Alamdarloo, et al.
Environmental Research (2019) Vol. 179, pp. 108770-108770
Closed Access | Times Cited: 133

Showing 1-25 of 133 citing articles:

COVID-19 Outbreak Prediction with Machine Learning
Sina Ardabili, Amir Mosavi, Pedram Ghamisi, et al.
Algorithms (2020) Vol. 13, Iss. 10, pp. 249-249
Open Access | Times Cited: 321
Susceptibility Mapping of Soil Water Erosion Using Machine Learning Models
Amirhosein Mosavi, Farzaneh Sajedi Hosseini, Bahram Choubin, et al.
Water (2020) Vol. 12, Iss. 7, pp. 1995-1995
Open Access | Times Cited: 144
BIM adoption in sustainability, energy modelling and implementing using ISO 19650: A review
Xingchen Pan, Abdul Mateen Khan, Sayed M. Eldin, et al.
Ain Shams Engineering Journal (2023) Vol. 15, Iss. 1, pp. 102252-102252
Open Access | Times Cited: 52
Ensemble models of GLM, FDA, MARS, and RF for flood and erosion susceptibility mapping: a priority assessment of sub-basins
Amirhosein Mosavi, Mohammad Golshan, Saeid Janizadeh, et al.
Geocarto International (2020) Vol. 37, Iss. 9, pp. 2541-2560
Closed Access | Times Cited: 113
Susceptibility Prediction of Groundwater Hardness Using Ensemble Machine Learning Models
Amirhosein Mosavi, Farzaneh Sajedi Hosseini, Bahram Choubin, et al.
Water (2020) Vol. 12, Iss. 10, pp. 2770-2770
Open Access | Times Cited: 83
A Novel GIS-Based Random Forest Machine Algorithm for the Spatial Prediction of Shallow Landslide Susceptibility
Viet-Hung Dang, Nhat‐Duc Hoang, Le-Mai-Duyen Nguyen, et al.
Forests (2020) Vol. 11, Iss. 1, pp. 118-118
Open Access | Times Cited: 78
Susceptibility mapping of groundwater salinity using machine learning models
Amirhosein Mosavi, Farzaneh Sajedi Hosseini, Bahram Choubin, et al.
Environmental Science and Pollution Research (2020) Vol. 28, Iss. 9, pp. 10804-10817
Closed Access | Times Cited: 72
Bim-based energy analysis and optimization using insight 360 (case study)
Ahmed M. Maglad, Moustafa Houda, Raid Alrowais, et al.
Case Studies in Construction Materials (2022) Vol. 18, pp. e01755-e01755
Open Access | Times Cited: 70
Artificial Intelligence models for prediction of the tide level in Venice
Francesco Granata, Fabio Di Nunno
Stochastic Environmental Research and Risk Assessment (2021) Vol. 35, Iss. 12, pp. 2537-2548
Closed Access | Times Cited: 62
Modeling, optimization and understanding of adsorption process for pollutant removal via machine learning: Recent progress and future perspectives
Wentao Zhang, Wenguang Huang, Jie Tan, et al.
Chemosphere (2022) Vol. 311, pp. 137044-137044
Open Access | Times Cited: 60
Flood susceptibility mapping using meta-heuristic algorithms
Alireza Arabameri, Amir Seyed Danesh, M. Santosh, et al.
Geomatics Natural Hazards and Risk (2022) Vol. 13, Iss. 1, pp. 949-974
Open Access | Times Cited: 57
Predicting shear wave velocity from conventional well logs with deep and hybrid machine learning algorithms
Meysam Rajabi, Omid Hazbeh, Shadfar Davoodi, et al.
Journal of Petroleum Exploration and Production Technology (2022) Vol. 13, Iss. 1, pp. 19-42
Open Access | Times Cited: 57
Time series-based groundwater level forecasting using gated recurrent unit deep neural networks
Haiping Lin, Amin Gharehbaghi, Qian Zhang, et al.
Engineering Applications of Computational Fluid Mechanics (2022) Vol. 16, Iss. 1, pp. 1655-1672
Open Access | Times Cited: 52
Improving Monthly Rainfall Forecast in a Watershed by Combining Neural Networks and Autoregressive Models
Albenis Pérez–Alarcón, Daniel Garcia-Cortes, José C. Fernández‐Alvarez, et al.
Environmental Processes (2022) Vol. 9, Iss. 3
Closed Access | Times Cited: 47
BIM-based architectural analysis and optimization for construction 4.0 concept (a comparison)
Jie Zhang, Xuping Zhu, Abdul Mateen Khan, et al.
Ain Shams Engineering Journal (2023) Vol. 14, Iss. 6, pp. 102110-102110
Open Access | Times Cited: 38
COVID-19 Outbreak Prediction with Machine Learning
Sina Ardabili, Amir Mosavi, Pedram Ghamisi, et al.
(2020)
Open Access | Times Cited: 70
Towards an Ensemble Machine Learning Model of Random Subspace Based Functional Tree Classifier for Snow Avalanche Susceptibility Mapping
Amirhosein Mosavi, Ataollah Shirzadi, Bahram Choubin, et al.
IEEE Access (2020) Vol. 8, pp. 145968-145983
Open Access | Times Cited: 65
Machine learning information fusion in Earth observation: A comprehensive review of methods, applications and data sources
Sancho Salcedo‐Sanz, Pedram Ghamisi, María Piles, et al.
Information Fusion (2020) Vol. 63, pp. 256-272
Open Access | Times Cited: 58
Mass wasting susceptibility assessment of snow avalanches using machine learning models
Bahram Choubin, Moslem Borji, Farzaneh Sajedi Hosseini, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 55
Machine learning methods for imbalanced data set for prediction of faecal contamination in beach waters
M Bourel, Ángel M. Segura, Carolina Crisci, et al.
Water Research (2021) Vol. 202, pp. 117450-117450
Closed Access | Times Cited: 53
Asthma-prone areas modeling using a machine learning model
Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi‐Niaraki, Soo-Mi Choi
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 48
Improving Results of Existing Groundwater Numerical Models Using Machine Learning Techniques: A Review
Cristina Di Salvo
Water (2022) Vol. 14, Iss. 15, pp. 2307-2307
Open Access | Times Cited: 29
COVID-19 Outbreak Prediction with Machine Learning
Sina Ardabili, Amir Mosavi, Pedram Ghamisi, et al.
(2020)
Open Access | Times Cited: 49
Establishment of Landslide Groundwater Level Prediction Model Based on GA-SVM and Influencing Factor Analysis
Ying Cao, Kunlong Yin, Chao Zhou, et al.
Sensors (2020) Vol. 20, Iss. 3, pp. 845-845
Open Access | Times Cited: 44
A Hybrid Landslide Displacement Prediction Method Based on CEEMD and DTW-ACO-SVR—Cases Studied in the Three Gorges Reservoir Area
Junrong Zhang, Huiming Tang, Tao Wen, et al.
Sensors (2020) Vol. 20, Iss. 15, pp. 4287-4287
Open Access | Times Cited: 43
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