Open Access
MATEC Web Conf.
Volume 355, 2022
2021 International Conference on Physics, Computing and Mathematical (ICPCM2021)
Article Number 02022
Number of page(s) 7
Section Mathematical Science and Application
Published online 12 January 2022
  1. JHu, S S Wen, D F Hu. Analysis, comparison and application of common methods of power load forecasting. Hubei electric power, vol. 32, no.2, pp.13–15, 2008. [Google Scholar]
  2. D X Niu, Z H Gu, M Xing. Research on SVM Short-term Load Forecasting Method Based on Data Mining. Proceedings of the CSEE, vol. 26, no.18, pp.6–12, 2006. [Google Scholar]
  3. S L Qiao. Short-term Traffic Flow Prediction based on deep learning. Qingdao University, Qingdao, 2018. [Google Scholar]
  4. Wang F, Tax D M J. Survey on the attention based RNN model and its applications in computer vision[J]. ar Xiv preprint ar Xiv:1601.06823, 2016. [Google Scholar]
  5. X J Zhu, H L Li, X Q Lu. An improved Attention-Based LSTM feature selection mode. Journal of Beijing Information Science and Technology University, vol. 33, no.2, pp.54–59, 2018. [Google Scholar]
  6. J X Lu, Q P Zhang, Z H Yang. Short-term load forecasting method based on CNNLSTM hybrid neural network model. Automation of Electric Power Systems, vol. 48, no.3, pp.131–137, 2019. [Google Scholar]

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