Prediction liquidated damages via ensemble machine learning model: towards sustainable highway construction projects

HIGHLIGHTS

• who: Odey Alshboul et al. from the Department of Civil Engineering, Faculty of Engineering, The Hashemite University, POBox , have published the research: Prediction Liquidated Damages via Ensemble Machine Learning Model: Towards Sustainable Highway Construction Projects, in the Journal: Sustainability 2022, 14, 9303. of /2022/
• what: This paper effort sought to develop an ensemble machine learning technique (EMLT) that combines algorithms of the Extreme Gradient Boosting (XGBoost) Categorical Boosting (CatBoost) k-Nearest Neighbor (kNN) Light Gradient Boosting Machine (LightGBM) Artificial Neural Network (ANN) and Decision Tree (DT) for the of LDs in highway Key attributes are . . .
  

   

  

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