Soft-computing modeling and multiresponse optimization for nutrient removal process from municipal wastewater using microalgae
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The SVR model had prediction error less than 3%.
“The SVR model had a prediction error of less than 3%, highlighting its effectiveness in balancing nutrient ratios for optimal growth.”
From Harnessing Artificial Intelligence to Revolutionize Microalgae Biotechnology: Unlocking Sustainable Solutions for High-Value Compounds and Carbon Neutrality (2025) · cites this paper as [32]
Hossain et al. (2022a) applied SVR with GA to optimize N:P ratio for Chlorella kessleri in municipal wastewater, identifying optimal N:P 6:1 and achieving nutrient removal efficiencies over 93% at 29.3 °C and continuous light.
“For instance, Hossain et al. (2022a) [32] applied SVR combined with a GA to optimize the nitrogen–phosphorus (N:P) ratio for Chlorella kessleri in municipal wastewater treatment. Their model identified an optimal N:P ratio of 6:1, achieving nutrient removal efficiencies of over 93% under conditions of 29.3 °C and continuous light (24/0 h/h).”
From Harnessing Artificial Intelligence to Revolutionize Microalgae Biotechnology: Unlocking Sustainable Solutions for High-Value Compounds and Carbon Neutrality (2025) · cites this paper as [32]
Cites
Kuhn, M., & Johnson, K. (2013) · doi:10.1007/978-1-4614-6849-3 · Cited by 6,788 · see citing works
Practical Bayesian Optimization of Machine Learning Algorithms
Snoek, J., Larochelle, H., & Adams, R. P. (2012) · arXiv · doi:10.48550/arxiv.1206.2944 · Cited by 6,691 · see citing works
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Microalgae cultivation in photobioreactors: sustainable solutions for a greener future
Abdur Razzak, S., Bahar, K., Islam, K. M. O., Haniffa, A. K., Faruque, M. O., Hossain, S. M. Z., & Hossain, M. M. (2024) · Green Chemical Engineering · doi:10.1016/j.gce.2023.10.004 · Cited by 366 · see citing works
Self-citationOruganti, R. K., Biji, A. P., Lanuyanger, T., Show, P. L., Sriariyanun, M., Upadhyayula, V. K. K., Gadhamshetty, V., & Bhattacharyya, D. (2023) · Science of The Total Environment · doi:10.1016/j.scitotenv.2023.162797 · Cited by 211 · see citing works
Machine learning for microalgae detection and utilization
Ning, H., Li, R., & Zhou, T. (2022) · Frontiers in Marine Science · doi:10.3389/fmars.2022.947394 · Cited by 83 · see citing works
Wu, Y., Shan, L., Zhao, W., & Lu, X. (2025) · Marine Drugs · doi:10.3390/md23050184 · Cited by 59 · see citing works
- Authors
- Hossain, S. M. Z., Sultana, N., Jassim, M. S., Coskuner, G., Hazin, L. M., Razzak, S. A., & Hossain, M. M.
- Venue
- Journal of Water Process Engineering
- Publisher
- Elsevier BV
- Published
- 2022-02
- Volume
- 45
- Pages
- 102490
- ISSN
- 2214-7144
- Cited by
- 53
- References
- 2
- Language
- en
- Licence
- Funders
- Kingdom of Saudi Arabia Ministry of Education
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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