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External constraints of neural cognition for CIMB stock closing price prediction
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نویسنده
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vui c.s. ,on c.k. ,soon g.k. ,alfred r. ,anthony p.
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منبع
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pertanika journal of science and technology - 2017 - دوره : 25 - شماره : S.June - صفحه:29 -38
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چکیده
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This paper investigates the accuracy of feedforward neural network (ffnn) with different external parameters in predicting the closing price of a particular stock. specifically,the feedforward neural network was trained using levenberg-marquardt backpropagation algorithm to forecast the cimb stock’s closing price in the kuala lumpur stock exchange (klse). the results indicate that the use of external parameters can improve the accuracy of the stock’s closing price. © 2017 universiti putra malaysia press.
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کلیدواژه
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Artificial neural network (ANNS); Backpropagation; Feedforward neural network (FFNN); Levenberg-marquardt algorithm; Macroeconomic parameters; Stock market forecasting
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آدرس
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faculty of informatics and computing,universiti malaysia sabah,kota kinabalu,sabah, Malaysia, faculty of informatics and computing,universiti malaysia sabah,kota kinabalu,sabah, Malaysia, faculty of informatics and computing,universiti malaysia sabah,kota kinabalu,sabah, Malaysia, faculty of informatics and computing,universiti malaysia sabah,kota kinabalu,sabah, Malaysia, department of applied computing,faculty of environment,society and design,lincoln university,christchurch, New Zealand
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Authors
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