On forecasting non-renewable energy production with uncertainty quantification: A case study of the Italian energy market
作者：
Highlights：
• New model for predicting the amount of non-renewable energy produced in Italy.
• The model uses mostly publicly available information sources.
• The experiments allow us to assess that GBRT is the best model for this task.
• Experimentally investigation of the possibility of identifying hard cases.
• KNN is the only technique that is able to identify hard cases.
摘要
•New model for predicting the amount of non-renewable energy produced in Italy.•The model uses mostly publicly available information sources.•The experiments allow us to assess that GBRT is the best model for this task.•Experimentally investigation of the possibility of identifying hard cases.•KNN is the only technique that is able to identify hard cases.
论文关键词：Energy production forecasting,Machine learning applications
论文评审过程：Received 22 October 2021, Revised 6 March 2022, Accepted 17 March 2022, Available online 26 March 2022, Version of Record 30 March 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.116936
