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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:

Deep learning ensembles for accurate fog-related low-visibility events forecasting
C. Peláez‐Rodríguez, Jorge Pérez-Aracíl, A. de Lopez-Diz, et al.
Neurocomputing (2023) Vol. 549, pp. 126435-126435
Open Access | Times Cited: 18

Showing 18 citing articles:

Analysis, characterization, prediction, and attribution of extreme atmospheric events with machine learning and deep learning techniques: a review
Sancho Salcedo‐Sanz, Jorge Pérez-Aracíl, Guido Ascenso, et al.
Theoretical and Applied Climatology (2023) Vol. 155, Iss. 1, pp. 1-44
Open Access | Times Cited: 28
Atmospheric Visibility and Cloud Ceiling Predictions with Hybrid IIS-LSTM Integrated Model: Case Studies for Fiji’s Aviation Industry
Shiveel Raj, Ravinesh C. Deo, Ekta Sharma, et al.
IEEE Access (2024) Vol. 12, pp. 72530-72543
Open Access | Times Cited: 4
Dempster-Shafer ensemble learning framework for air pollution nowcasting
Trung H. Le, Huynh Nguyen, Q. P. Ha, et al.
E3S Web of Conferences (2025) Vol. 626, pp. 01003-01003
Open Access
Bike sharing and cable car demand forecasting using machine learning and deep learning multivariate time series approaches
C. Peláez‐Rodríguez, Jorge Pérez-Aracíl, Dušan Fister, et al.
Expert Systems with Applications (2023) Vol. 238, pp. 122264-122264
Open Access | Times Cited: 10
Efficient prediction of fog-related low-visibility events with Machine Learning and evolutionary algorithms
C. Peláez‐Rodríguez, Jorge Pérez-Aracíl, C. Casanova‐Mateo, et al.
Atmospheric Research (2023) Vol. 295, pp. 106991-106991
Open Access | Times Cited: 9
ABCNet: A comprehensive highway visibility prediction model based on attention, Bi-LSTM and CNN
Wen Li, Xuekun Yang, Guowu Yuan, et al.
Mathematical Biosciences & Engineering (2024) Vol. 21, Iss. 3, pp. 4397-4420
Open Access | Times Cited: 2
Deep learning applications in the Internet of Things: a review, tools, and future directions
Parisa Raoufi, Atefeh Hemmati, Amir Masoud Rahmani
Evolutionary Intelligence (2024)
Closed Access | Times Cited: 2
Sofia Airport Visibility Estimation with Two Machine-Learning Techniques
Nikolay Penov, Guergana Guerova
Remote Sensing (2023) Vol. 15, Iss. 19, pp. 4799-4799
Open Access | Times Cited: 6
ATCNet: A Novel Approach for Predicting Highway Visibility Using Attention-Enhanced Transformer–Capsule Networks
Wen Li, Xuekun Yang, Guowu Yuan, et al.
Electronics (2024) Vol. 13, Iss. 5, pp. 920-920
Open Access | Times Cited: 1
Unveiling the nexus between atmospheric visibility, remotely sensed pollutants, and climatic variables across diverse topographies: A data-driven exploration empowered by artificial intelligence
Sadaf Javed, Muhammad Imran Shahzad, Imran Shahid
Atmospheric Pollution Research (2024) Vol. 15, Iss. 9, pp. 102200-102200
Closed Access | Times Cited: 1
Improvement in the Forecasting of Low Visibility over Guizhou, China, Based on a Multi-Variable Deep Learning Model
Dongpo He, Yuetong Wang, Yuanzhi Tang, et al.
Atmosphere (2024) Vol. 15, Iss. 7, pp. 752-752
Open Access | Times Cited: 1
Machine learning analysis of PM1 impact on visibility with comprehensive sensitivity evaluation of concentration, composition, and meteorological factors
Grzegorz Majewski, Bartosz Szeląg, Wioletta Rogula‐Kozłowska, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Event Classification on Subsea Pipeline Inspection Data Using an Ensemble of Deep Learning Classifiers
Truong Dang, Tien Thanh Nguyen, Alan Wee‐Chung Liew, et al.
Cognitive Computation (2024) Vol. 17, Iss. 1
Open Access | Times Cited: 1
Improving classification‐based nowcasting of radiation fog with machine learning based on filtered and preprocessed temporal data
Adrian Schütz, Adrian Schütz, Jörg Bendix, et al.
Quarterly Journal of the Royal Meteorological Society (2023) Vol. 150, Iss. 759, pp. 577-596
Open Access | Times Cited: 2
Research on the Fusion of FY4A Satellite Data and Station Observation Data for Heavy Fog Recognition
Yao Zhenhai, Chuanhui Wang, Chun Jiang
Research Square (Research Square) (2024)
Open Access
Optimizing Nominal Current Output for Aeronautical Ground Lighting Using Machine Learning and Meteorological Data
W. M. R. Jamaludin, N. H. Nik Ali, Wan Mazlina Wan Mohamed, et al.
IEEE Access (2024) Vol. 12, pp. 100073-100085
Open Access
VisNet: Spatiotemporal self-attention-based U-Net with multitask learning for joint visibility and fog occurrence forecasting
Jinah Kim, Jieun Cha, Taekyung Kim, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 136, pp. 108967-108967
Closed Access
Research on the fusion of FY4A satellite data and station observation data for heavy fog recognition
Zhenhai Yao, Chuanhui Wang, Chun Jiang
Theoretical and Applied Climatology (2024) Vol. 156, Iss. 1
Closed Access
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