# Application of Machine Learning Models in Optimizing Wastewater Treatment Processes: A Review
## 3 Materials and Methods
### Methodology Used for Machine Learning Models Applied in Wastewater Treatment Processes
Of the 300 articles, 144 journals contained them. From these 144, the ones that contained three or more articles were selected. High-impact journals (e.g., nature, science, water research) are not only looking for solving an environmental problem but also consider other fields (groundbreaking discoveries, global environmental impacts) while accommodating to ML applied to WWTT. On the other hand, the _Journal of Water Process Engineering_ and _Water_ focus on water treatment technologies and are expected to be more friendly to ML applications in this specialized field. Journals such as _Water_ and _Journal of Water Process Engineering_ specifically address the community of water treatment engineering and thus are desired publications for researchers studying ML applications in WWTPs. Figure 4: Graph of citations associated with 300 articles according to age-adjusted citations. The following section investigates the selection process, from an extensive collection of 300 works to the final count of 80. These 80 papers contain predictions about processes related to wastewater treatment. PRISMA 2020 guidelines were used to represent this selection process visually. These guidelines are a widely accepted standard for clarity and \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Journal** & **2018** & **2019** & **2020** & **2021** & **2022** & **2023** & **2024** & **2025** & **Total** \\ \hline Water & & 1 & & 3 & 8 & 14 & 3 & 29 \\ \hline Journal of Water Process & & 2 & 3 & 4 & 1 & 4 & & 14 \\ Engineering & & & & & & & & \\ \hline Journal of Environmental Management & 1 & & 1 & 2 & 2 & 4 & & 10 \\ \hline Sustainability & & & 1 & 2 & 2 & 4 & & 9 \\ \hline Chemical Engineering & 1 & 2 & 3 & 2 & & & & 8 \\ Research \& Design & & & & & & & 8 \\ \hline Environmental Monitoring & 1 & 1 & 1 & 1 & 1 & 1 & 2 & 8 \\ and Assessment & & & & & & & & \\ \hline Applied Sciences & & & & & 1 & 3 & 3 & 7 \\ \hline Science of the Total & & & 1 & 4 & 1 & & & 7 \\ Environment & & & 1 & 1 & & 3 & & 6 \\ \hline Chemosphere & 1 & & & 1 & 3 & 2 & & 6 \\ Environmental Science and & & & 1 & 1 & 1 & 1 & & 5 \\ Pollution Research & & & & & & & & \\ \hline Journal of Cleaner Production & 1 & & 1 & 1 & 1 & 1 & 5 \\ \hline Journal of Environmental & & & & 1 & & 3 & 1 & 5 \\ Chemical Engineering & & & & & 1 & & 2 & 2 & 5 \\ \hline Processes & & & & 1 & & 3 & & 5 \\ \hline Water Research & 1 & & 1 & & 3 & & & 4 \\ \hline Chemical Engineering Journal & 1 & & 3 & & & & & 4 \\ \hline Engineering Applications of & & & & & 1 & & 2 & 1 & 4 \\ Artificial Intelligence & & & & & & & 3 & & 4 \\ \hline IEEE Access & & 1 & & & & & & & \\ \hline Desalination & & & & 1 & 1 & 1 & & 3 \\ \hline Elsevier eBooks & & & 1 & & & & & 2 & 3 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Distribution of published articles on wastewater treatment in ML context by journal and year (2018–2025). Figure 5: Distribution of published articles on wastewater treatment in ML context by Year (2011–2025). thoroughness in reporting systematic reviews. The PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow chart is a comprehensive and standardized framework that documents the literature search and selection of studies [64]. It helps organize the data and clarifies how systematic review authors choose studies and why they include (or exclude) certain studies. The sections in Figure 6 are presented in detail below. The three sections represent stages of the selection process. The articles were selected from databases and with the help of other methods. 1. Identification Section  
* Left side (Databases and Registers):
* 300 records were identified from 5 databases (Web of Science, Scopus, IEEE Xplore, PubMed, arXiv).