Tao Jiang, Kaal Joeri, Jian Liang, Jiang Liu, Yao-Ling Zhang, Ding-Yong Wang, Shi-Qiang Wei, Zheng Zhao
[Use of the Nitrogen/Carbon Ratio (N/C) and Two End-Member Sources Mixing Model to Identify the Origins of Dissolved Organic Matter from Soils in the Water-Level Fluctuation Zones of the Three Gorges Reservoir]
Huan jing ke xue= Huanjing kexue
pyrolysis thermochemical conversion approach transforming plastic waste energy tremendous potential manage exponentially increasing plastic waste however understanding process kinetics fundamental engineering sustainable process conventional analysis techniques provide insights influence characteristics feedstock process kinetics present study exemplifies efficacy using machine learning predictive modeling pyrolysis waste plastics understand complexities interrelations predictor variables influence activation energy activation energy pyrolysis waste plastics evaluated using machine learning models namely random forest xgboost catboost adaboost regression models feature selection based multicollinearity data hyperparameter tuning models utilizing randomizedsearchcv conducted random forest model outperformed models coefficient determination r2 value 0941 root mean square error rmse value 1469 mean absolute error mae value 866 testing dataset explainable artificial intelligencebased feature importance plot summary plot shapely additive explanations projected fixed carbon content ash content conversion value carbon content significant parameters model order fixed carbon carbon ash content degree conversion present study highlighted potential machine learning powerful tool understand influence characteristics plastic waste degree conversion activation energy process essential designing largescale operations future scaleup process