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Improved and optimized recurrent neural network based on PSO and its application in stock price prediction

Soft Computing volume 27, pages 3461–3476 (2023)Cite this article

Abstract

In order to improve the stock price prediction effect, based on the improved PSO algorithm, this paper constructs a stock price prediction model through neural network. Based on the idea of avoiding particles falling into the same local solution as much as possible and always keeping the particles with a certain diversity, in order to improve the global search ability of the algorithm in the early stage of evolution and the local search ability in the later stage of the evolution, the adaptive adjustment of inertial weight is proposed, and the algorithm is improved by combining with neural network. In addition, on the basis of the improved algorithm, this paper constructs a stock price prediction system based on neural network. Finally, this paper designs experiments to verify the function of the model from the perspectives of stock data collection and processing, and stock price prediction accuracy, and draw statistical graphs based on the statistical research results. The results of the research show that the system constructed in this paper has a certain practical effect.

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Funding

No funding support were received by the co-authors.

Author information

Authors and Affiliations

  1. Yangtze River Economic Research Center, Chongqing Technology and Business University, Chongqing, 400067, China

    Fuwei Yang & Jingjing Chen

  2. International Business School, Chongqing Technology and Business University, Chongqing, 400067, China

    Fuwei Yang & Jingjing Chen

  3. Chongqing Tongyu Technology Co., Ltd., Chongqing, 401120, China

    Yicen Liu

Authors
  1. Fuwei Yang
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  2. Jingjing Chen
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  3. Yicen Liu
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Contributions

FY presented the concept and wrote the manuscript with the help of all of the authors. JC created the model and carried out the validation and resources. YL performed the experimental analysis and assisted in the review and editing of the manuscript.

Corresponding author

Correspondence to Fuwei Yang.

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Communicated by Vicente Garcia Diaz.

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Yang, F., Chen, J. & Liu, Y. Improved and optimized recurrent neural network based on PSO and its application in stock price prediction. Soft Comput 27, 3461–3476 (2023). https://doi.org/10.1007/s00500-021-06113-5

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  • DOI: https://doi.org/10.1007/s00500-021-06113-5

Keywords

  • PSO
  • Cyclic neural network
  • Stock price
  • Prediction model
  • Artificial intelligence
  • BP network