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- W3100187460 abstract "Based on the generalized additive model, we propose a CPP-GAM algorithm which transforms the non-linear problem into a linear one. We apply this algorithm to predict the closing price of international and domestic stocks. We train the history data of stocks through back-fitting algorithm. In order to make the effect of prediction better, we get trend lines based on the method of changing point prediction, the regressive algorithm of OLS, and the Fourier series. Through a large number of empirical data analysis, we found the predictive accuracy of CPP-GAM algorithm is 89%, which is 15% higher than that of RBN, SVM, SSA-SVM and so on." @default.
- W3100187460 created "2020-11-23" @default.
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- W3100187460 date "2020-10-01" @default.
- W3100187460 modified "2023-10-18" @default.
- W3100187460 title "Stock Price Prediction Based on CPP-GAM" @default.
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- W3100187460 doi "https://doi.org/10.1088/1742-6596/1624/4/042056" @default.
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