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Electricity price forecasting with a BED (Bivariate EMD Denoising) methodology
Citations
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- Ding, Yishan, 2018. "A novel decompose-ensemble methodology with AIC-ANN approach for crude oil forecasting," Energy, Elsevier, vol. 154(C), pages 328-336.
- Xiong, Xiaoping & Qing, Guohua, 2023. "A hybrid day-ahead electricity price forecasting framework based on time series," Energy, Elsevier, vol. 264(C).
- Zhang, Jinliang & Tan, Zhongfu & Wei, Yiming, 2020. "An adaptive hybrid model for short term electricity price forecasting," Applied Energy, Elsevier, vol. 258(C).
- Chang, Zihan & Zhang, Yang & Chen, Wenbo, 2019. "Electricity price prediction based on hybrid model of adam optimized LSTM neural network and wavelet transform," Energy, Elsevier, vol. 187(C).
- Afanasyev, Dmitriy O. & Fedorova, Elena A., 2019. "On the impact of outlier filtering on the electricity price forecasting accuracy," Applied Energy, Elsevier, vol. 236(C), pages 196-210.
- Alexopoulos, Thomas A., 2017. "The growing importance of natural gas as a predictor for retail electricity prices in US," Energy, Elsevier, vol. 137(C), pages 219-233.
- Yanbing Lin & Hongyuan Luo & Deyun Wang & Haixiang Guo & Kejun Zhu, 2017. "An Ensemble Model Based on Machine Learning Methods and Data Preprocessing for Short-Term Electric Load Forecasting," Energies, MDPI, vol. 10(8), pages 1-16, August.
- He, Kaijian & Chen, Yanhui & Tso, Geoffrey K.F., 2018. "Forecasting exchange rate using Variational Mode Decomposition and entropy theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 15-25.
- Chai, Shanglei & Li, Qiang & Abedin, Mohammad Zoynul & Lucey, Brian M., 2024. "Forecasting electricity prices from the state-of-the-art modeling technology and the price determinant perspectives," Research in International Business and Finance, Elsevier, vol. 67(PA).
- Hakan Acaroğlu & Fausto Pedro García Márquez, 2021. "Comprehensive Review on Electricity Market Price and Load Forecasting Based on Wind Energy," Energies, MDPI, vol. 14(22), pages 1-23, November.
- Usman Zafar & Neil Kellard & Dmitri Vinogradov, 2022. "Multistage optimization filter for trend‐based short‐term forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 345-360, March.
- Jasiński, Tomasz, 2020. "Use of new variables based on air temperature for forecasting day-ahead spot electricity prices using deep neural networks: A new approach," Energy, Elsevier, vol. 213(C).
- Florian Ziel & Rafal Weron, 2016. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate models," HSC Research Reports HSC/16/08, Hugo Steinhaus Center, Wroclaw University of Technology.
- Liu, Luyao & Bai, Feifei & Su, Chenyu & Ma, Cuiping & Yan, Ruifeng & Li, Hailong & Sun, Qie & Wennersten, Ronald, 2022. "Forecasting the occurrence of extreme electricity prices using a multivariate logistic regression model," Energy, Elsevier, vol. 247(C).
- Gabrielli, Paolo & Wüthrich, Moritz & Blume, Steffen & Sansavini, Giovanni, 2022. "Data-driven modeling for long-term electricity price forecasting," Energy, Elsevier, vol. 244(PB).
- Wang, Deyun & Luo, Hongyuan & Grunder, Olivier & Lin, Yanbing & Guo, Haixiang, 2017. "Multi-step ahead electricity price forecasting using a hybrid model based on two-layer decomposition technique and BP neural network optimized by firefly algorithm," Applied Energy, Elsevier, vol. 190(C), pages 390-407.
- He, Kaijian & Chen, Yanhui & Tso, Geoffrey K.F., 2017. "Price forecasting in the precious metal market: A multivariate EMD denoising approach," Resources Policy, Elsevier, vol. 54(C), pages 9-24.
- Fang Guo & Shangyun Deng & Weijia Zheng & An Wen & Jinfeng Du & Guangshan Huang & Ruiyang Wang, 2022. "Short-Term Electricity Price Forecasting Based on the Two-Layer VMD Decomposition Technique and SSA-LSTM," Energies, MDPI, vol. 15(22), pages 1-20, November.
- Qing Peng & Fenghua Wen & Xu Gong, 2021. "Time‐dependent intrinsic correlation analysis of crude oil and the US dollar based on CEEMDAN," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 834-848, January.
- Bhatia, Kushagra & Mittal, Rajat & Varanasi, Jyothi & Tripathi, M.M., 2021. "An ensemble approach for electricity price forecasting in markets with renewable energy resources," Utilities Policy, Elsevier, vol. 70(C).
- Huang, Junwei & Xiao, Qingtai & Liu, Jingjing & Wang, Hua, 2019. "Modeling heat transfer properties in an ORC direct contact evaporator using RBF neural network combined with EMD," Energy, Elsevier, vol. 173(C), pages 306-316.
- Niu, Hongli & Xu, Kunliang & Liu, Cheng, 2021. "A decomposition-ensemble model with regrouping method and attention-based gated recurrent unit network for energy price prediction," Energy, Elsevier, vol. 231(C).
- Zhang, Wenbin & Tian, Lixin & Wang, Minggang & Zhen, Zaili & Fang, Guochang, 2016. "The evolution model of electricity market on the stable development in China and its dynamic analysis," Energy, Elsevier, vol. 114(C), pages 344-359.
- Lu, Shibao & Zhang, Xiaoling & Shang, Yizi & Li, Wei & Skitmore, Martin & Jiang, Shuli & Xue, Yangang, 2018. "Improving Hilbert–Huang transform for energy-correlation fluctuation in hydraulic engineering," Energy, Elsevier, vol. 164(C), pages 1341-1350.
- Siddiqui, Atiq W. & Basu, Rounaq, 2020. "An empirical analysis of relationships between cyclical components of oil price and tanker freight rates," Energy, Elsevier, vol. 200(C).
- Ziel, Florian & Weron, Rafał, 2018.
"Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks,"
Energy Economics, Elsevier, vol. 70(C), pages 396-420.
- Florian Ziel & Rafal Weron, 2018. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks," Papers 1805.06649, arXiv.org.