A multi-task learning method for multi-energy load forecasting based on synthesis correlation analysis and load participation factor
Authors:
- Mao TanMTMao Tan
- Chengchen LiaoCLChengchen Liao
- Jie ChenJCJie Chen
- Yijia CaoYCYijia Cao
- Rui WangRWRui Wang
- Yongxin SuYSYongxin Su
Top Cited Papers
- 5 May 2023
- journal article
- research article
- Published by Elsevier in Applied Energy
- Vol. 343
Abstract
No abstract availableKeywords
This publication has 25 references indexed in Scilit:
- Planning Multiple Energy Systems Toward Low-Carbon Society: A Decentralized ApproachIEEE Transactions on Smart Grid, 2018
- A VVWBO-BVO-based GM (1,1) and its parameter optimization by GRA-IGSA integration algorithm for annual power load forecastingPLOS ONE, 2018
- Review and prospect of integrated demand response in the multi-energy systemApplied Energy, 2017
- An overview of multi-task learningNational Science Review, 2017
- A Review of Short Term Load Forecasting using Artificial Neural Network ModelsProcedia Computer Science, 2015
- Short-term heat load forecasting for single family housesEnergy and Buildings, 2013
- The use of grey relational analysis in solving multiple attribute decision-making problemsComputers & Industrial Engineering, 2008
- Short-Term Load Forecasting for the Holidays Using Fuzzy Linear Regression MethodIEEE Transactions on Power Systems, 2005
- Multitask LearningMachine Learning, 1997
- Short-term load forecastingProceedings of the IEEE, 1987