Machine learning models for predicting the residual value of heavy construction equipment: An evaluation of modified decision tree, LightGBM, and XGBoost regression
Machine learning models for predicting the residual value of heavy construction equipment: An evaluation of modified decision tree, LightGBM, and XGBoost regression
Ali Shehadeh,Odey Alshboul,R. Mamlook,Ola Hamedat
2021 · DOI: 10.1016/J.AUTCON.2021.103827
356 Citations
TLDR
Three Machine Learning-based methods of Modified Decision Tree (MDT), LightGBM, and XGBoost regressions are proposed to predict construction equipment's residual value to help advancing automation as a coherent field of research within the construction industry.