Stock market prediction of S&P 500 via combination of improved BCO approach and BP neural network
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摘要
The paper proposed an improved bacterial chemotaxis optimization (IBCO), which is then integrated into the back propagation (BP) artificial neural network to develop an efficient forecasting model for prediction of various stock indices. Experiments show its better performance than other methods in learning ability and generalization.
论文关键词:Bacterial chemotaxis optimization (BCO),Stock index prediction,Back propagation neural network (BPNN)
论文评审过程:Available online 28 November 2008.
论文官网地址:https://doi.org/10.1016/j.eswa.2008.11.028