Abstract
The stock market is an investment market that is full of risk and return, to obtain higher benefits while reducing the risk of investors is the pursuit of the goal, the radial basis function network with its simple structure, excellent global approximation properties to arouse the wide attention of scholars. This paper is based on RBF neural network, through the examples of the empirical analysis; the results show that, the network has good learning and generalization ability, and achieved good results in the stock market trend prediction.
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Ji, T., Che, W., Zong, N. (2014). Stock Market Forecast Based on RBF Neural Network. In: Wen, Z., Li, T. (eds) Practical Applications of Intelligent Systems. Advances in Intelligent Systems and Computing, vol 279. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54927-4_92
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DOI: https://doi.org/10.1007/978-3-642-54927-4_92
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