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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:

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

Showing 26-50 of 53 citing articles:

Sequence-based machine learning method for predicting the effects of phosphorylation on protein-protein interactions
Xiaokun Hong, Jiyang Lv, Zhengxin Li, et al.
International Journal of Biological Macromolecules (2023) Vol. 243, pp. 125233-125233
Closed Access | Times Cited: 8
Prediction of total organic carbon and E. coli in rivers within the Milwaukee River basin using machine learning methods
Nabila Nafsin, Jin Li
Environmental Science Advances (2022) Vol. 2, Iss. 2, pp. 278-293
Open Access | Times Cited: 12
Modeling Job Satisfaction of Peruvian Basic Education Teachers Using Machine Learning Techniques
Luis Alberto Holgado-Apaza, Edgar Eloy Carpio Vargas, Hugo D. Calderon-Vilca, et al.
Applied Sciences (2023) Vol. 13, Iss. 6, pp. 3945-3945
Open Access | Times Cited: 7
Hybrid optimized RF model of seismic resilience of buildings in mountainous region based on hyperparameter tuning and SMOTE
Haijia Wen, Jinnan Wu, Chi Zhang, et al.
Journal of Building Engineering (2023) Vol. 71, pp. 106488-106488
Closed Access | Times Cited: 7
Influence of resampling techniques on Bayesian network performance in predicting increased algal activity
Maryam Zeinolabedini, Heather J. Lacey, Lucy Marshall, et al.
Water Research (2023) Vol. 244, pp. 120558-120558
Open Access | Times Cited: 7
Novel Intelligent Control Framework for WWTP Optimization To Achieve Stable and Sustainable Operation
Kuanliang Feng, Zihao Zhao, Mengyan Li, et al.
ACS ES&T Engineering (2022) Vol. 2, Iss. 11, pp. 2086-2094
Closed Access | Times Cited: 11
Machine Learning-Based Early Warning Level Prediction for Cyanobacterial Blooms Using Environmental Variable Selection and Data Resampling
Jin Hwi Kim, Hankyu Lee, Seohyun Byeon, et al.
Toxics (2023) Vol. 11, Iss. 12, pp. 955-955
Open Access | Times Cited: 6
Enhancing Machine Learning Performance in Estimating CDOM Absorption Coefficient via Data Resampling
Jinuk Kim, Jin Hwi Kim, Wonjin Jang, et al.
Remote Sensing (2024) Vol. 16, Iss. 13, pp. 2313-2313
Open Access | Times Cited: 2
Trajectory-based fish event classification through pre-training with diffusion models
Noemi Canovi, Benjamin A. Ellis, Tonje Knutsen Sørdalen, et al.
Ecological Informatics (2024) Vol. 82, pp. 102733-102733
Open Access | Times Cited: 2
Part-Scale Microstructure Prediction for Laser Powder Bed Fusion Ti-6Al-4V Using a Hybrid Mechanistic and Machine Learning Model
B. Whitney, Anthony G. Spangenberger, Theron Rodgers, et al.
Additive manufacturing (2024) Vol. 94, pp. 104500-104500
Closed Access | Times Cited: 2
Application of Oversampling Techniques for Enhanced Transverse Dispersion Coefficient Estimation Performance Using Machine Learning Regression
Sunmi Lee, Inhwan Park
Water (2024) Vol. 16, Iss. 10, pp. 1359-1359
Open Access | Times Cited: 1
A Machine Learning Framework for Enhanced Assessment of Sewer System Operation under Data Constraints and Skewed Distributions
Wan-Xin Yin, Yuqi Wang, Jia-Qiang Lv, et al.
ACS ES&T Engineering (2024)
Closed Access | Times Cited: 1
Synergizing Convergent Cross-Mapping and Machine learning for reliable daily forecasting of riverine chlorophyll-a concentration
Jing Tian, Gangsheng Wang, Huang Sheng, et al.
Journal of Hydrology (2024), pp. 132072-132072
Closed Access | Times Cited: 1
Assessing the environmental determinants of micropollutant contamination in streams using explainable machine learning and network analysis
Min Jeong Ban, Dong Hoon Lee, Byung-Tae Lee, et al.
Chemosphere (2024) Vol. 370, pp. 144041-144041
Closed Access | Times Cited: 1
Binary classification of users of electronic cigarettes and smokeless tobacco through biomarkers to assess similarity with current and former smokers: machine learning applied to the population assessment of tobacco and health study
Hiromi Ohara, Shigeaki Ito, Yuichiro Takanami
BMC Public Health (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 3
Machine-Learning-Based Approach To Assessing Water Quality in a Specific Basin: The Case of Wujingang Basin
Shubo Zhang, Ruonan He, Qian Wang, et al.
ACS ES&T Water (2023) Vol. 4, Iss. 3, pp. 1014-1023
Closed Access | Times Cited: 2
Simulación del proceso precipitación-escorrentía con paso diario: comparación de los modelos GR4J, SWAT y random forest
Federico Vilaseca, Santiago Narbondo, Christian Chreties, et al.
Ribagua (2023) Vol. 10, Iss. 1, pp. 31-47
Open Access | Times Cited: 1
Assessing the Utility of Shellfish Sanitation Monitoring Data for Long-Term Estuarine Water Quality Analysis
Natalie Chazal, Megan Carr, Andrew Haines, et al.
Authorea (Authorea) (2024)
Open Access
Comparative Evaluation of Imbalanced Data Management Techniques for Solving Classification Problems on Imbalanced Datasets
Tanawan Watthaisong, Khamron Sunat, Nipotepat Muangkote
Statistics Optimization & Information Computing (2024) Vol. 12, Iss. 2, pp. 547-570
Open Access
A Variational Mode Decomposition Analysis and Prediction Simulation of DO in the Water Environment of the Chengdu Area, China
Mei Li, Deke Wang, Rui Xu, et al.
Water (2024) Vol. 16, Iss. 10, pp. 1405-1405
Open Access
Assessing the performance of machine learning algorithms for analyzing land use changes in the Hyrcanian forests of Iran
Zeinab Aminzadeh, اباذر اسمعلی عوری, Raoof Mostafazadeh, et al.
Environmental Science and Pollution Research (2024)
Closed Access
Predicting Surface Water Bacteria Levels Using Transfer Learning and Domain Adaptation
A Abd Elahi, David Shumway, Megan Kowalcyk, et al.
2021 IEEE International Conference on Big Data (Big Data) (2024), pp. 1-10
Closed Access
Addressing gaps in data on drinking water quality through data integration and machine learning: evidence from Ethiopia
Alemayehu A. Ambel, Robert Bain, Tefera Bekele Degefu, et al.
npj Clean Water (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 1
Probabilistic mapping of imbalanced data for groundwater contamination using classification algorithms: Performance and reliability
Yang Qiu, Aiguo Zhou, Hanxiang Xiong, et al.
Groundwater for Sustainable Development (2024) Vol. 28, pp. 101393-101393
Closed Access
Comparison of two machine learning frameworks for predicting aggregatory behaviour of sharks
Michael W. Wade, Mark Fisher, Philip Matich
Journal of Applied Ecology (2022) Vol. 59, Iss. 11, pp. 2767-2778
Closed Access | Times Cited: 1

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