Open Access
| Issue |
SHS Web Conf.
Volume 170, 2023
2023 International Conference on Digital Economy and Management Science (CDEMS 2023)
|
|
|---|---|---|
| Article Number | 03019 | |
| Number of page(s) | 4 | |
| Section | Enterprise Operation and Human Resource Management | |
| DOI | https://doi.org/10.1051/shsconf/202317003019 | |
| Published online | 14 June 2023 | |
- Peng Y., Liu Y.H. and Zhang R.F.(2019) Stock price prediction modeling and analysis based on LSTM[J]. Computer Engineering, 55(11): 209–212. [Google Scholar]
- Song G., Zhang Y.F., Bao F.X. and Qin C. (2019) Stock prediction model based on particle swarm optimization LSTM[J]. Journal of Beijing University of Aeronautics and Astronautics, 45(12): 2533–2542. [Google Scholar]
- Kim, T., Kim, H.Y. (2019) Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data. PLoS ONE, 14. [Google Scholar]
- S. Hochreiter and J. Schmidhuber, (1997) ”Long Short-Term Memory,” in Neural Computation, 9(8): 1735–1780. [CrossRef] [Google Scholar]
- J. Kennedy and R. Eberhart.(1995) “Particle swarm optimization,” Proceedings of ICNN’95-International Conference on Neural Networks, Perth, WA, Australia, 4: 1942–1948. [CrossRef] [Google Scholar]
- Yin J., Dai C.P., Yuan and Hu W.P.(2023) Short term power load forecasting based on APSO-LSTM model[J]. Science and Technology & Innovation, (02): 47–51. [CrossRef] [Google Scholar]
- Xu F.Q., Zou D.X. and Li C.(2023) Improvedparticle swarm algorithm with Circle mapping and sine cosine factor introduced[J/OL]. Computer Engineering: 1–13. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.