E3S Web Conf.
Volume 235, 20212020 International Conference on New Energy Technology and Industrial Development (NETID 2020)
|Number of page(s)||5|
|Section||Analysis on the Development of Intelligent Supply Chain and Internet Digital Industrialization|
|Published online||03 February 2021|
Research on the Prediction Method of Stock Price Based on RBF Neural Network Optimization Algorithm
Rutgers Business School, Rutgers University, Newark, USA
2 School of Business, Shandong University, Weihai, Weihai, China
With the development of social economy, people pay more and more attention to investment and financial management. However, due to the strong volatility of the stock market, it is difficult to accurately predict the future trend of stock and the investment risk is very high. This paper proposes an optimization algorithm based on RBF neural network to predict the stock price. On the basis of RBF neural network, K-means clustering algorithm is introduced to optimize the network parameters, improve the training speed and prediction accuracy of the algorithm, and set corresponding evaluation indexes to evaluate the performance of the algorithm. The method proposed in this paper is applied to the stock prediction of stock market, and the closing price of several stocks in a period of time is predicted. The experimental results show that the method proposed in this paper has better prediction accuracy than other methods, and it is practical in the field of stock prediction.
© The Authors, published by EDP Sciences, 2021
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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