A machine learning approach to wastewater treatment: Gaussian process regression and Monte Carlo analysis
Year: 2025
Type: article
Abstract: = 0.0277). The superiority of the GPR model was validated by comparing the Gaussian Process Regression Mean (RPAE value) of 0.92689 with the Polynomial Regression Mean (RPAE value of 2.2947). Besides, the simultaneous interpretation of the effects of the three predictors on the response variable was enabled using the GPR model, which is impossible when interpreting the polynomial regression model. Therefore, the GPR offers superior modeling, deeper insights, and reliable predictions, proving it to be a more sustainable and effective method for pollutant degradation in wastewater treatment than polynomial modeling.
Source: Nanoscale Advances
DOI: 10.1039/d4na01064g
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,962
Awards: G1256483571, G2016893528, G2062598255
OpenAlex ID: W4410768257