Long-Term Electricity Demand Forecasting in the Steel Complex Micro-Grid Electricity Supply Chain—A Coupled Approach
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- Majed A. Alotaibi, 2022. "Machine Learning Approach for Short-Term Load Forecasting Using Deep Neural Network," Energies, MDPI, vol. 15(17), pages 1-23, August.
- Yun Duan, 2022. "A Novel Interval Energy-Forecasting Method for Sustainable Building Management Based on Deep Learning," Sustainability, MDPI, vol. 14(14), pages 1-18, July.
- Bidong Liu & Jakub Nowotarski & Tao Hong & Rafal Weron, 2015. "Probabilistic load forecasting via Quantile Regression Averaging on sister forecasts," HSC Research Reports HSC/15/01, Hugo Steinhaus Center, Wroclaw University of Technology.
- V. Y. Kondaiah & B. Saravanan, 2022. "Short-Term Load Forecasting with a Novel Wavelet-Based Ensemble Method," Energies, MDPI, vol. 15(14), pages 1-17, July.
- Chujie Tian & Jian Ma & Chunhong Zhang & Panpan Zhan, 2018. "A Deep Neural Network Model for Short-Term Load Forecast Based on Long Short-Term Memory Network and Convolutional Neural Network," Energies, MDPI, vol. 11(12), pages 1-13, December.
- Jakub Nowotarski & Rafał Weron, 2015.
"Computing electricity spot price prediction intervals using quantile regression and forecast averaging,"
Computational Statistics, Springer, vol. 30(3), pages 791-803, September.
- Jakub Nowotarski & Rafal Weron, 2013. "Computing electricity spot price prediction intervals using quantile regression and forecast averaging," HSC Research Reports HSC/13/12, Hugo Steinhaus Center, Wroclaw University of Technology.
- Ashfaq Ahmad & Nadeem Javaid & Abdul Mateen & Muhammad Awais & Zahoor Ali Khan, 2019. "Short-Term Load Forecasting in Smart Grids: An Intelligent Modular Approach," Energies, MDPI, vol. 12(1), pages 1-21, January.
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Keywords
electricity supply chain; long short-term memory neural network (LSTM); hyper-parameter; ELATLBO; wavelet transform; micro-grid; Bayesian optimization;All these keywords.
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