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Combining Deep Learning and Multiresolution Analysis for Stock Market Forecasting

  • Published:2021 Issue: Volume:9 Page:13099-13111
  • ISSN:2169-3536
  • Container-title:IEEE Access
  • language:
  • Short-container-title:IEEE Access

Author:

Althelaya Khaled A.,Mohammed Salahadin A.ORCID,El-Alfy El-Sayed M.ORCID

Funder

King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Cited by 29 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Application of symmetric uncertainty and emperor penguin — Grey wolf optimisation for feature selection in motor fault classification;IET Electric Power Applications;2024-08-07

2. A novel Deep Reinforcement Learning based automated stock trading system using cascaded LSTM networks;Expert Systems with Applications;2024-05

3. Wavelet decomposition-based multi-stage feature engineering and optimized ensemble classifier for stock market prediction;The Engineering Economist;2024-03-20

4. Trend Encoder with Attentive Neural Process: Node Performance Extrapolation for Non-Time-Series Datasets;2024 International Conference on Computing, Networking and Communications (ICNC);2024-02-19

5. Research on Fintech Stock Index Forecasting Methods Based on Big Data Artificial Intelligence;Proceedings of the 2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence;2024-01-19
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