ZHUJing-yi,HUANGYuan-xi,YIQi-hang,et al.Prediction of Reactivity between Potassium Permanganate and Organic Pollutants Based on Machine Learning[J].China Water & Wastewater,2024,40(11):41-48.
Prediction of Reactivity between Potassium Permanganate and Organic Pollutants Based on Machine Learning
China Water & Wastewater[ISSN:1000-4062/CN:12-1073/TU]
volume:
第40卷
Number:
第11期
Page:
41-48
Column:
Date of publication:
2024-06-01
- Keywords:
- potassium permanganate; organic pollutant; reaction rate constant; machine learning; random forest (RF) algorithm; SHAP
- Abstract:
- Potassium permanganate (KMnO4) has strong oxidation ability and stable properties, and is a common emergency oxidation agent for treating micro-polluted raw water and sudden pollution in waterworks. The reaction rate constant (k value) of potassium permanganate to organic pollutants is an important parameter to evaluate its reactivity with organic pollutants. However, there are many kinds of organic pollutants, and it is time?consuming and costly to determine a large number of k values simply by means of experiments or theoretical calculations. This paper collected a total of 574 organic pollutants, and employed four algorithms, such as random forest (RF), neural network (NN), extreme gradient boosting (XGBoost) and support vector machine (SVM), with molecular fingerprints (MFs) and pH serving as input features to establish machine learning (ML) models for predicting k values. The four models all had good robustness and prediction ability, among which the RF model demonstrated the best prediction performance (R2test=0.818, RMSEtest=0.476). The SHAP (SHapley Additive exPlanations) method was utilized to analyze the RF model, revealing that electron-donating groups and pH exerted the most significant influence on the prediction of k value. This indicated that the model correctly learned the relationship between k values and the chemical structures of organic pollutants. Simultaneously, the application domain (AD) of the RF model was calculated to validate its suitability. The developed model can accurately and conveniently determine the k values, aiding in understanding the reactivity of potassium permanganate with organic pollutants.
Last Update:
2024-06-01