The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Stock price prediction based on deep neural networks
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Citations
Cites
LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126
Deep learning in neural networks: an overview
Schmidhuber, J. (2015) · Neural Networks · doi:10.1016/j.neunet.2014.09.003 · Cited by 18,570
Greff, K., Srivastava, R. K., Koutnik, J., Steunebrink, B. R., & Schmidhuber, J. (2017) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2016.2582924 · Cited by 6,955
Time series forecasting using a hybrid ARIMA and neural network model
Zhang, G. P. (2003) · Neurocomputing · doi:10.1016/s0925-2312(01)00702-0 · Cited by 4,428
Towards End-To-End Speech Recognition with Recurrent Neural Networks
Graves, A., & Jaitly, N. (2014) · Cited by 1,861
Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500
Krauss, C., Do, X. A., & Huck, N. (2017) · European Journal of Operational Research · doi:10.1016/j.ejor.2016.10.031 · Cited by 750
Economic prediction using neural networks: the case of IBM daily stock returns
White (1988) · IEEE International Conference on Neural Networks · doi:10.1109/icnn.1988.23959 · Cited by 698
Deep learning for event-driven stock prediction
Ding, X., Zhang, Y., Liu, T., & Duan, J. (2015) · International Conference on Artificial Intelligence · Cited by 685
A Bayesian regularized artificial neural network for stock market forecasting
Ticknor, J. L. (2013) · Expert Systems with Applications · doi:10.1016/j.eswa.2013.04.013 · Cited by 517
A deep learning ensemble approach for crude oil price forecasting
Zhao, Y., Li, J., & Yu, L. (2017) · Energy Economics · doi:10.1016/j.eneco.2017.05.023 · Cited by 380
Cited by
VT-ADL: A Vision Transformer Network for Image Anomaly Detection and Localization
Mishra, P., Verk, R., Fornasier, D., Piciarelli, C., & Foresti, G. L. (2021) · 2021 IEEE 30th International Symposium on Industrial Electronics (ISIE) · doi:10.1109/isie45552.2021.9576231 · Cited by 462
“A system which can perform this task in an intelligent way is hugely in demand, as its applications range from video surveillance [1] to defect segmentation [2], [3], inspection [2], quality control [4], medical imagining [5], financial transactions [6] etc.”
Background
Metadata
- Authors
- Yu, P., & Yan, X.
- Venue
- Neural Computing and Applications
- Published
- 2019-04-17
- Volume
- 32
- Issue
- 6
- Pages
- 1609-1628
- ISSN
- 0941-0643 (ISSN-L)
- 1433-3058
- OpenAlex
- W2936404407
- Cited by
- 373
- References
- 19
- FWCI
- 30.05
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Yu, P., & Yan, X. (2020). Stock price prediction based on deep neural networks. Neural Computing and Applications. https://doi.org/10.1007/s00521-019-04212-x
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
