Forecasting stock indices using radial basis function neural networks optimized by artificial fish swarm algorithm

Stock index forecasting is a hot issue in the financial arena. As the movements of stock indices are non-linear and subject to many internal and external factors, they pose a great challenge to researchers who try to predict them. In this paper, we select a radial basis function neural network (RBFN...

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Vydáno v:	Knowledge-based systems Ročník 24; číslo 3; s. 378 - 385
Hlavní autoři:	Shen, Wei, Guo, Xiaopen, Wu, Chao, Wu, Desheng
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.04.2011
Témata:	Artificial fish swarm algorithm Data mining K-means clustering algorithm Radial basis function neural network Shanghai Stock Exchange Index K-means clustering algorithm Shanghai Stock Exchange Index Artificial fish swarm algorithm Data mining Radial basis function neural network
ISSN:	0950-7051, 1872-7409
On-line přístup:	Získat plný text
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