A novel ensemble method for residential electricity demand forecasting based on a novel sample simulation strategy
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DOI: 10.1016/j.energy.2020.118265
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References listed on IDEAS
- Li, Song & Goel, Lalit & Wang, Peng, 2016. "An ensemble approach for short-term load forecasting by extreme learning machine," Applied Energy, Elsevier, vol. 170(C), pages 22-29.
- Xing, Yazhou & Zhang, Su & Wen, Peng & Shao, Limin & Rouyendegh, Babak Daneshvar, 2020. "Load prediction in short-term implementing the multivariate quantile regression," Energy, Elsevier, vol. 196(C).
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Cited by:
- Zhang, Yunfei & Zhou, Zhihua & Liu, Junwei & Yuan, Jianjuan, 2022. "Data augmentation for improving heating load prediction of heating substation based on TimeGAN," Energy, Elsevier, vol. 260(C).
- Imani, Maryam, 2021. "Electrical load-temperature CNN for residential load forecasting," Energy, Elsevier, vol. 227(C).
- Zheyu He & Rongheng Lin & Budan Wu & Xin Zhao & Hua Zou, 2023. "Pre-Attention Mechanism and Convolutional Neural Network Based Multivariate Load Prediction for Demand Response," Energies, MDPI, vol. 16(8), pages 1-13, April.
- Mansour, Shaza H. & Azzam, Sarah M. & Hasanien, Hany M. & Tostado-Veliz, Marcos & Alkuhayli, Abdulaziz & Jurado, Francisco, 2024. "Wasserstein generative adversarial networks-based photovoltaic uncertainty in a smart home energy management system including battery storage devices," Energy, Elsevier, vol. 306(C).
- Luo, Zheng & Lin, Xiaojie & Qiu, Tianyue & Li, Manjie & Zhong, Wei & Zhu, Lingkai & Liu, Shuangcui, 2024. "Investigation of hybrid adversarial-diffusion sample generation method of substations in district heating system," Energy, Elsevier, vol. 288(C).
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Keywords
Electricity demand forecasting; Improved coupled generative adversarial stacked auto-encoder (ICoGASA); Integrated forecast; Self-organizing map (SOM); Memristor array (MA);All these keywords.
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