ArticleScientific reports2025
Harnessing AI to revolutionize photocatalytic degradation of Tetracycline via optimized UV/ZrO
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- ZrORSC advances · 2026Review
- Predictive modelling of tetracycline removal by I-Bi/BiScientific reports · 2026Article
- Photodegradation of ciprofloxacin by tannin-barium titanate catalysts and evaluation via artificial neural network modeling approaches.Scientific reports · 2026Article
- Machine learning framework for oxytetracycline removal using nanostructured cupric oxide supported on magnetic chitosan alginate biocomposite.Scientific reports · 2025Article
- Modeling methylene blue removal using magnetic chitosan carboxymethyl cellulose multiwalled carbon nanotube composite with genetic algorithms and regression techniques.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper assesses the presentation of Gradient Boosting Regression (GBR), Ridge Regression (RR), and Particle Swarm Optimization (PSO) models in improving the photocatalytic destruction of antibiotic utilizing a UV/ZrO₂/NaOCl system. The GBR model indicated the strength of exhibited precision, with high R² and Explained Variance Score (EVS) esteems, however gave indications of overfitting. Remarkably, the RR model obtained had many significant values and the model had a high data fitness with an R² of 0.81; however, error bars were observed in some areas that could be optimized by fine-tuning. Feature significance examination indicated that X2, X1, and X5 fundamentally affected the model's performance. At last, PSO was instrumental in finding the ideal limit mix to support removal performance. Altogether the presented models help to improve the photocatalytic degradation process and provide useful tools for further investigation in this field.
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Registered trials
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