Research on stock index forecast based on improved BP neural network model

Hao Cheng; Quan Zhou

doi:10.1117/12.2637095

15 June 2022 Research on stock index forecast based on improved BP neural network model

Hao Cheng, Quan Zhou

Proceedings Volume 12285, International Conference on Advanced Algorithms and Neural Networks (AANN 2022); 122850M (2022) https://doi.org/10.1117/12.2637095
Event: International Conference on Advanced Algorithms and Neural Networks (AANN 2022), 2022, Zhuhai, China

Abstract

In order to solve the problem of the BP neural network falling into local minimum and slow network convergence rate, the genetic algorithm is used to optimize the weights and thresholds of the network, and the learning rate is dynamically adjusted according to the total error change of the network output. The improved BP neural network model is used to predict and analyze the Shanghai composite index. The empirical study shows that the improved BP neural network prediction model can accelerate the convergence rate of the algorithm and effectively improve the prediction accuracy.

Citation Download Citation

Hao Cheng and Quan Zhou "Research on stock index forecast based on improved BP neural network model", Proc. SPIE 12285, International Conference on Advanced Algorithms and Neural Networks (AANN 2022), 122850M (15 June 2022); https://doi.org/10.1117/12.2637095

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