Multivariable short-term electricity price forecasting using artificial intelligence and multi-input multi-output scheme

Ping Jiang(University of Electronic Science and Technology of China), Xiaojia Huang(Lanzhou University), Ying Nie(Guiyang Medical University), Jianzhou Wang(Dongbei University of Finance and Economics)
Energy Economics
December 14, 2022
10.1016/j.eneco.2022.106471
Cited by 76

Related Papers

A combined forecasting model for time series: Application to short-term wind speed forecasting
|Applied Energy|2019|305
A combined forecasting system based on statistical method, artificial neural networks, and deep learning methods for short-term wind speed forecasting
|Energy|2020|234
The study and application of a novel hybrid forecasting model – A case study of wind speed forecasting in China
|Applied Energy|2015|167
A hybrid forecasting system based on fuzzy time series and multi-objective optimization for wind speed forecasting
|Applied Energy|2018|164
Ensemble forecasting system for short-term wind speed forecasting based on optimal sub-model selection and multi-objective version of mayfly optimization algorithm
|Expert Systems with Applications|2021|159