Stock market prediction of S&P 500 via combination of improved BCO approach and BP neural network

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Abstract

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. © 2008 Elsevier Ltd. All rights reserved.

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Yudong, Z., & Lenan, W. (2009). Stock market prediction of S&P 500 via combination of improved BCO approach and BP neural network. Expert Systems with Applications, 36(5), 8849–8854. https://doi.org/10.1016/j.eswa.2008.11.028

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