Publications by authors named "Qiangbin Liu"
J Hazard Mater
December 2024
Article Synopsis
- * A machine learning approach was developed to improve screening and contamination prediction, comparing the effectiveness of Support Vector Machine (SVM), Random Forest (RF), and Back Propagation Neural Network (BPNN) algorithms.
- * The results indicated that the RF model was most accurate for screening, while BPNN was best for predicting groundwater pollution, with key influencing factors being the distribution coefficient (K), decay coefficient (λ), and initial leakage concentration ratio (C/C).
