Time Series Prediction Using Artificial Neural Network and Its Application Mackey-Glass Equation and Stock Index
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Abstract
This paper presents time series prediction using artificial neural network and its application Mackey-Glass equation and stock index. The prediction method is a neural network with nonlinear autoregressive network with exogenous inputs (NARX) that utilizes the weight and bias values to adjust the optimized network parameter through learning algorithms. The optimization is achieved through the smallest mean square value. Test for prediction of time series is done by two methods: the Mackey-Glass and real SET50 stock index. The proposed method shows very low errors and can also be useful re real-world applications in enterprises.
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References
“SET50 & SET100Indices Rule”, ฝ่ายพัฒนาธุรกิจ–ตราสารหนี้และอื่นๆตลาดหลักทรัพย์แห่งประเทศไทย, มกราคม 2556.
Wilton.W.T. Fok, IAENG, Vincent.W.L. Tam, Hon N, “Computational Neural Network forGlobal Stock Indexes Prediction”, Proceedings of the World Congress on Engineering 2008 Vol II, WCE 2008, July 2 - 4, 2008, London, U.K.
Mike P. Hanias, and Panayiotis G. Curtis, “Time Series Prediction of DollarEuro Exchange Rate Index”, International Research Journal of Finance and Economics, ISSN 1450-2887, Issue 15, Euro Journals Publishing, 2008.
Ali Moeini Associate Professor, “Forecasting Gold Price via Chaotic Models and Lyapunov Exponent”, Faculty of Engineering, University of Tehran, Mehdi Ahrari Econometrics Researcher, PartoKarimi Bs in Apply Mathematics, Faculty of Sciences, University of Tehran
ร้อยโทสุวรรณ บุญวิจิตร, “ระบบการพยากรณ์ราคาข้าวเปลือกเจ้านาปี 5 เปอร์เซ็นต์โดยใช้โครงข่ายใยประสาทเทียมผ่านเครือข่ายอินเทอร์เน็ต”, คณะเทคโนโลยีสารสนเทศ สถาบันเทคโนโลยีพระจอมเกล้าพระนครเหนือ 2549.
เกียรติศักด์ จันทร์แก้ว และ สุพจน์นิตย์ สุวัฒน์ “การเปรียบเทียบผลการพยากรณ์อนุกรมเวลาราคาปาล์มน้ำมันโดยการใช้โครงข่ายประสาทเทียมฟังก์ชันพหุนามและโครงข่ายประสาทเทียม”, คณะวิทยาศาสตร์ สาขาระบบสารสนเทศเพื*อการจัดการ คณะเทคโนโลยีสารสนเทศ มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ 2011.