An XGBoost-SHAP Model for Energy Demand Prediction With Boruta–Lasso Feature Selection

An XGBoost-SHAP Model for Energy Demand Prediction With Boruta–Lasso Feature Selection

Energy demand prediction is essential in ensuring national energy security, promoting high-quality economic development, advancing sustainable development, optimizing the energy structure, and achieving dual carbon goals. In recent years, machine learning (ML) algorithms have been extensively used i...

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Bibliographic Details
Main Authors: Yiwen Wang, Weibin Cheng, Yuting Jin, Jifei Li, Yantian Yang, Shaobing Hu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Energy demand prediction
interpretability
feature selection
Boruta-Lasso model
XGBoost
SHAP
Online Access:https://ieeexplore.ieee.org/document/11098871/
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