Optimize stock price variation prediction via DOE and BPNN

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題名:	Optimize stock price variation prediction via DOE and BPNN
作者:	謝玲芬 Hsieh, Ling-Feng
貢獻者:	運輸科技與物流管理學系 Transportation Technology and Logistics Management
關鍵詞:	Stock price forecasting;Back-propagation neural network;Design of experiment;Parameter optimization t
日期:	2010
上傳時間:	2014-06-27 00:21:38 (UTC+8)
摘要:	Stock price variation predictions are at the core of many research issues, and neural networks (NNs) are widely applied and were proven to be more efficient than time series forecasting for stock price forecasting. However, this type of research always de
顯示於類別:	[運輸科技與物流管理學系] 研討會論文

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