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• W2077494141 abstract "This paper explores the application of a wavelet neural network (WNN), whose hidden layer is comprised of neurons with adjustable wavelets as activation functions, to stock prediction. We discuss some basic rationales behind technical analysis, and based on which, inputs of the prediction system are carefully selected. This system is tested on Istanbul Stock Exchange National 100 Index and compared with traditional neural networks. The results show that the WNN can achieve very good prediction accuracy." @default.
• W2077494141 created "2016-06-24" @default.
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• W2077494141 date "2013-05-29" @default.
• W2077494141 modified "2023-10-17" @default.
• W2077494141 title "Wavelet neural networks for stock trading" @default.
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• W2077494141 doi "https://doi.org/10.1117/12.2018040" @default.
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