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Short-run electricity load forecasting with combinations of stationary wavelet transforms

Citations

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Cited by:

  1. Christina C. Bartenschlager & Jens O. Brunner, 2019. "Reaching for the stars: attention to multiple testing problems and method recommendations using simulation for business research," Journal of Business Economics, Springer, vol. 89(4), pages 447-479, June.
  2. Feng Gao & Jie Song & Xueyan Shao, 2025. "Short-term interval-valued load forecasting with a combined strategy of iHW and multioutput machine learning," Annals of Operations Research, Springer, vol. 346(3), pages 2009-2033, March.
  3. Vincenzo Loia & Stefania Tomasiello & Alfredo Vaccaro & Jinwu Gao, 2020. "Using local learning with fuzzy transform: application to short term forecasting problems," Fuzzy Optimization and Decision Making, Springer, vol. 19(1), pages 13-32, March.
  4. Yuri S. Popkov & Alexey Yu. Popkov & Yuri A. Dubnov & Dimitri Solomatine, 2020. "Entropy-Randomized Forecasting of Stochastic Dynamic Regression Models," Mathematics, MDPI, vol. 8(7), pages 1-20, July.
  5. Wang, Chuang & Zhao, Haishen & Liu, Yang & Fan, Guojin, 2024. "Minute-level ultra-short-term power load forecasting based on time series data features," Applied Energy, Elsevier, vol. 372(C).
  6. 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.
  7. Lee, Juyong & Cho, Youngsang, 2022. "National-scale electricity peak load forecasting: Traditional, machine learning, or hybrid model?," Energy, Elsevier, vol. 239(PD).
  8. Zhang, Jinliang & Siya, Wang & Zhongfu, Tan & Anli, Sun, 2023. "An improved hybrid model for short term power load prediction," Energy, Elsevier, vol. 268(C).
  9. Mesbaholdin Salami & Farzad Movahedi Sobhani & Mohammad Sadegh Ghazizadeh, 2018. "Short-Term Forecasting of Electricity Supply and Demand by Using the Wavelet-PSO-NNs-SO Technique for Searching in Big Data of Iran’s Electricity Market," Data, MDPI, vol. 3(4), pages 1-26, October.
  10. Sen, Doruk & Tunç, K.M. Murat & Günay, M. Erdem, 2021. "Forecasting electricity consumption of OECD countries: A global machine learning modeling approach," Utilities Policy, Elsevier, vol. 70(C).
  11. Zhou, Cheng & Chen, Xiyang, 2019. "Predicting energy consumption: A multiple decomposition-ensemble approach," Energy, Elsevier, vol. 189(C).
  12. Sharifzadeh, Mahdi & Sikinioti-Lock, Alexandra & Shah, Nilay, 2019. "Machine-learning methods for integrated renewable power generation: A comparative study of artificial neural networks, support vector regression, and Gaussian Process Regression," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 513-538.
  13. Yajing Gao & Xiaojie Zhou & Jiafeng Ren & Zheng Zhao & Fushen Xue, 2018. "Electricity Purchase Optimization Decision Based on Data Mining and Bayesian Game," Energies, MDPI, vol. 11(5), pages 1-19, April.
  14. Daniel v{S}tifani'c & Jelena Musulin & Adrijana Miov{c}evi'c & Sandi Baressi v{S}egota & Roman v{S}ubi'c & Zlatan Car, 2020. "Impact of COVID-19 on Forecasting Stock Prices: An Integration of Stationary Wavelet Transform and Bidirectional Long Short-Term Memory," Papers 2007.02673, arXiv.org.
  15. Lintao Yang & Honggeng Yang & Haitao Liu, 2018. "GMDH-Based Semi-Supervised Feature Selection for Electricity Load Classification Forecasting," Sustainability, MDPI, vol. 10(1), pages 1-16, January.
  16. Kailai Ni & Jianzhou Wang & Guangyu Tang & Danxiang Wei, 2019. "Research and Application of a Novel Hybrid Model Based on a Deep Neural Network for Electricity Load Forecasting: A Case Study in Australia," Energies, MDPI, vol. 12(13), pages 1-30, June.
  17. Zhang, Jinliang & Wei, Yi-Ming & Li, Dezhi & Tan, Zhongfu & Zhou, Jianhua, 2018. "Short term electricity load forecasting using a hybrid model," Energy, Elsevier, vol. 158(C), pages 774-781.
  18. Miguel López & Sergio Valero & Carlos Sans & Carolina Senabre, 2020. "Use of Available Daylight to Improve Short-Term Load Forecasting Accuracy," Energies, MDPI, vol. 14(1), pages 1-14, December.
  19. Ding, Jia & Wang, Maolin & Ping, Zuowei & Fu, Dongfei & Vassiliadis, Vassilios S., 2020. "An integrated method based on relevance vector machine for short-term load forecasting," European Journal of Operational Research, Elsevier, vol. 287(2), pages 497-510.
  20. Dai, Yeming & Yang, Xinyu & Leng, Mingming, 2022. "Forecasting power load: A hybrid forecasting method with intelligent data processing and optimized artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
  21. Richard Bean, 2023. "Forecasting the Monash Microgrid for the IEEE-CIS Technical Challenge," Energies, MDPI, vol. 16(3), pages 1-23, January.
  22. Barja-Martinez, Sara & Aragüés-Peñalba, Mònica & Munné-Collado, Íngrid & Lloret-Gallego, Pau & Bullich-Massagué, Eduard & Villafafila-Robles, Roberto, 2021. "Artificial intelligence techniques for enabling Big Data services in distribution networks: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
  23. Guo-Feng Fan & Li-Ling Peng & Xiangjun Zhao & Wei-Chiang Hong, 2017. "Applications of Hybrid EMD with PSO and GA for an SVR-Based Load Forecasting Model," Energies, MDPI, vol. 10(11), pages 1-22, October.
  24. Wei, Nan & Yin, Lihua & Li, Chao & Wang, Wei & Qiao, Weibiao & Li, Changjun & Zeng, Fanhua & Fu, Lingdi, 2022. "Short-term load forecasting using detrend singular spectrum fluctuation analysis," Energy, Elsevier, vol. 256(C).
  25. Koch, Christopher & Hirth, Lion, 2019. "Short-term electricity trading for system balancing: An empirical analysis of the role of intraday trading in balancing Germany's electricity system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
  26. Tayab, Usman Bashir & Lu, Junwei & Yang, Fuwen & AlGarni, Tahani Saad & Kashif, Muhammad, 2021. "Energy management system for microgrids using weighted salp swarm algorithm and hybrid forecasting approach," Renewable Energy, Elsevier, vol. 180(C), pages 467-481.
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