MATEC Web Conf.
Volume 355, 20222021 International Conference on Physics, Computing and Mathematical (ICPCM2021)
|Number of page(s)||9|
|Section||Computing Methods and Computer Application|
|Published online||12 January 2022|
Computational intelligence model based on GA-BP neural network
Chengdu Polytechnic, Chengdu, PR China
* Corresponding author: firstname.lastname@example.org
Since the birth of the secondary stock market, the prediction of the stock price trend has become a research direction concerned by many people. Aiming at the problem of non-stationary and non-linear stock price forecasting, this paper builds a computational intelligence model to improve the neural network with genetic algorithm. The results show that, compared with other models, the GA-BP neural network model proposed in this article can effectively improve the prediction of the rise and fall of the HS300 index, and the withdrawal range is small when the market falls. The research of this paper enriches the method of financial time series data analysis, which can not only provide decision-making reference for investors, but also help to enhance the cognition of financial market rules. The model can significantly reduce the forecast error and improve the model fitting ability.
Key words: Stock market / Genetic algorithm / BP neural network / Prediction error
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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