EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 632 (2025) E3S Web Conf., 632 (2025) 02012 References
Open Access
Issue
E3S Web Conf.
Volume 632, 2025
The 5th Edition of Oriental Days for the Environment “Green Lab. Solution for Sustainable Development” (JOE5)
Article Number 02012
Number of page(s) 17
Section AI in Environmental Pollution & Health Risks Management
DOI https://doi.org/10.1051/e3sconf/202563202012
Published online 03 June 2025
  1. O.O. Akomolafe, T. Olorunsogo, E.C. Anyanwu, F. Osasona, J.O. Ogugua, and O.H. Daraojimba, «Air quality and public health: a review of urban pollution sources and mitigation measures», Eng. Sci. Technol. J., 5(2), 259-271 (2024). Doi: 10.51594/estj.v5i2.751. [CrossRef] [Google Scholar]
  2. D.-H. Nguyen, C.-H. Liao, X.-T. Bui, C.-S. Yuan, and C. Lin, « A Review on Analytical Approaches for Ambient Ozone Open Data in Taiwan », Curr. Pollut. Rep., 10(3), 374-386 (2024). Doi: 10.1007/s40726-024-00314-w. [CrossRef] [Google Scholar]
  3. T. Seesaard, K. Kamjornkittikoon, and C. Wongchoosuk, « A comprehensive review on advancements in sensors for air pollution applications », Sci. Total Environ., vol. 951, p. 175696 (2024), doi: 10.1016/j.scitotenv.2024.175696. [CrossRef] [Google Scholar]
  4. T. Feng, Y. Sun, Y. Shi, J. Ma, C. Feng, and Z. Chen, « Air pollution control policies and impacts: A review », Renew. Sustain. Energy Rev., 191, 114071 (2024). Doi: 10.1016/j.rser.2023.114071. [CrossRef] [Google Scholar]
  5. H. Irfan, « Air pollution and cardiovascular health in South Asia: A comprehensive review », Curr. Probl. Cardiol., 49(2), 102199 (2024). [CrossRef] [Google Scholar]
  6. M. Moghimi Dehkordi, Z. Pournuroz Nodeh, K. Soleimani Dehkordi, H. Salmanvandi, R. Rasouli Khorjestan, and M. Ghaffarzadeh, « Soil, air, and water pollution from mining and industrial activities: Sources of pollution, environmental impacts, and prevention and control methods », Results Eng. 23, 102729 (2024). Doi: 10.1016/j.rineng.2024.102729. [CrossRef] [Google Scholar]
  7. E. G. Obahiagbon et E. A. Kosoe, « Economic Dimensions of Air Pollution: Cost Analysis, Valuation, and Policy Impacts », in Sustainable Strategies for Air Pollution Mitigation, 133, in The Handbook of Environmental Chemistry, Cham: Springer Nature Switzerland, 111-139 (2024). [Google Scholar]
  8. T. Madan, S. Sagar, D. Virmani, D. Rastogi, and T. A. Tran, « Air Quality Prediction using Ensemble Classifiers and Single Decision Tree », J. Adv. Res. Appl. Sci. Eng. Technol., 52(1), 56-67 (2024). [CrossRef] [Google Scholar]
  9. Z. Sadriddin, R. R. Mekuria, and M. S. Gaso, « Machine Learning Models for Advanced Air Quality Prediction », in Proceedings of the International Conference on Computer Systems and Technologies 2024, Ruse Bulgaria: ACM, 51-56 (2024). Doi: 10.1145/3674912.3674915. [Google Scholar]
  10. P. Chaturvedi, « Air Quality Prediction System Using Machine Learning Models », Water. Air. Soil Pollut., 235(9), 578 (2024). [CrossRef] [Google Scholar]
  11. M. Imam, S. Adam, S. Dev, and N. Nesa, « Air quality monitoring using statistical learning models for sustainable environment », Intell. Syst. Appl., 22, 200333 (2024). Doi: 10.1016/j.iswa.2024.200333. [Google Scholar]
  12. R. Veeranjaneyulu, S. Boopathi, R. K. Kumari, A. Vidyarthi, J. S. Isaac, and V. Jaiganesh, « Air Quality Improvement and Optimisation Using Machine Learning Technique », in 2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI), Chennai, India: IEEE, 1-6 (2023). Doi: 10.1109/ACCAI58221.2023.10201168. [Google Scholar]
  13. M. Hardini, R. A. Sunarjo, M. Asfi, M. H. Riza Chakim, and Y. P. Ayu Sanjaya, « Predicting Air Quality Index using Ensemble Machine Learning », ADI J. Recent Innov. AJRI, 5(1Sp), 78-86 (2023). [CrossRef] [Google Scholar]
  14. D. Kothandaraman et al., « Intelligent Forecasting of Air Quality and Pollution Prediction Using Machine Learning », Adsorpt. Sci. Technol., 2022, 5086622 (2022). Doi: 10.1155/2022/5086622. [CrossRef] [Google Scholar]
  15. N. H. Van, P. Van Thanh, D. N. Tran, and D.-T. Tran, « A new model of air quality prediction using lightweight machine learning », Int. J. Environ. Sci. Technol., 20(3), 2983-2994 (2023). Doi: 10.1007/s13762-022-04185-w. [CrossRef] [Google Scholar]
  16. R. Murugan et N. Palanichamy, « Smart City Air Quality Prediction using Machine Learning », in 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS), Madurai, India: IEEE, 1048-1054 (2021). Doi: 10.1109/ICICCS51141.2021.9432074. [Google Scholar]
  17. A. Bekkar, B. Hssina, S. Douzi, and K. Douzi, « Air-pollution prediction in smart city, deep learning approach », J. Big Data, 8(1), 161 (2021). [CrossRef] [Google Scholar]
  18. W. Mao, W. Wang, L. Jiao, S. Zhao, and A. Liu, « Modeling air quality prediction using a deep learning approach: Method optimization and evaluation », Sustain. Cities Soc., 65, 102567 (2021). [CrossRef] [Google Scholar]
  19. M. Castelli, F. M. Clemente, A. Popovič, S. Silva, and L. Vanneschi, « A Machine Learning Approach to Predict Air Quality in California », Complexity, 2020, 1-23 (2020). Doi: 10.1155/2020/8049504. [Google Scholar]
  20. G. K. Kang, J. Z. Gao, S. Chiao, S. Lu, and G. Xie, « Air Quality Prediction: Big Data and Machine Learning Approaches », Int. J. Environ. Sci. Dev., vol. 9(1), 8-16 (2018). Doi: 10.18178/ijesd.2018.9.1.1066. [CrossRef] [Google Scholar]
  21. A. Perdana, A. Hermawan, and D. Avianto, « Analyze Important Features of PIMA Indian Database For Diabetes Prediction Using KNN », J. Sisfokom Sist. Inf. Dan Komput., 12(1), 70-75 (2023). [Google Scholar]
  22. « K-Nearest Neighbors (KNN) in Depth | by Tech-AI-Math | Artificial Intelligence in Plain English ». https://ai.plainenglish.io/k-nearest-neighbors-knn-769bd39514c6 [Google Scholar]
  23. « Why Is Logistic Regression a Classification Algorithm? | Built In ». https://builtin.com/machine-learning/logistic-regression-classification-algorithm [Google Scholar]
  24. T. Beghriche, M. Djerioui, Y. Brik, B. Attallah, and S. B. Belhaouari, « An Efficient Prediction System for Diabetes Disease Based on Deep Neural Network », Complexity, 2021(1), 6053824 (2021). [CrossRef] [Google Scholar]
  25. M. Y. Khan, A. Qayoom, M. S. Nizami, M. S. Siddiqui, S. Wasi, and S. M. K.-R. Raazi, « Automated Prediction of Good Dictionary EXamples (GDEX): A Comprehensive Experiment with Distant Supervision, Machine Learning, and Word Embedding‐Based Deep Learning Techniques », Complexity, 2021(1), 2553199 (2021). Doi: 10.1155/2021/2553199. [CrossRef] [Google Scholar]
  26. « Fully Explained Gradient Boosting Technique in Supervised Learning | Towards AI ». https://towardsai.net/p/machine-learning/fully-explained- gradient-boosting-technique-in-supervised-learning. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.