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題名 Fuzzy Forecasting with DNA Computing 作者 鄭至甫
Jeng, Jyh‐Fu貢獻者 科管智財所 日期 2006 上傳時間 7-Nov-2014 16:03:05 (UTC+8) 摘要 There are many forecasting techniques including: exponential smoothing, ARIMA model, GARCH model, neural networks and genetic algorithm, etc. Since financial time series may be influenced by many factors, conventional model based techniques and hard computing methods seem inadequate in the prediction. Those methods, however, have their drawbacks and advantages. In recent years, the innovation and improvement of forecasting techniques have caught more attention, and also provides indispensable information in decision-making process. In this paper, a new forecasting technique, named DNA forecasting, is developed. This may be of use to a nonlinear time series forecasting. The methods combined the mathematical, computational, and biological sciences. In the empirical study, we demonstrated a novel approach to forecast the exchange rates through DNA. The mean absolute forecasting accuracy method is defined and used in evaluating the performance of linguistic forecasting. The comparison with ARIMA model is also illustrated. 關聯 Lecture Notes in Computer Science, 4287, 324-336 資料類型 article DOI http://dx.doi.org/10.1007/11925903_25 dc.contributor 科管智財所 en_US dc.creator (作者) 鄭至甫 zh_TW dc.creator (作者) Jeng, Jyh‐Fu en_US dc.date (日期) 2006 en_US dc.date.accessioned 7-Nov-2014 16:03:05 (UTC+8) - dc.date.available 7-Nov-2014 16:03:05 (UTC+8) - dc.date.issued (上傳時間) 7-Nov-2014 16:03:05 (UTC+8) - dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/71244 - dc.description.abstract (摘要) There are many forecasting techniques including: exponential smoothing, ARIMA model, GARCH model, neural networks and genetic algorithm, etc. Since financial time series may be influenced by many factors, conventional model based techniques and hard computing methods seem inadequate in the prediction. Those methods, however, have their drawbacks and advantages. In recent years, the innovation and improvement of forecasting techniques have caught more attention, and also provides indispensable information in decision-making process. In this paper, a new forecasting technique, named DNA forecasting, is developed. This may be of use to a nonlinear time series forecasting. The methods combined the mathematical, computational, and biological sciences. In the empirical study, we demonstrated a novel approach to forecast the exchange rates through DNA. The mean absolute forecasting accuracy method is defined and used in evaluating the performance of linguistic forecasting. The comparison with ARIMA model is also illustrated. en_US dc.format.extent 118 bytes - dc.format.mimetype text/html - dc.language.iso en_US - dc.relation (關聯) Lecture Notes in Computer Science, 4287, 324-336 en_US dc.title (題名) Fuzzy Forecasting with DNA Computing en_US dc.type (資料類型) article en dc.identifier.doi (DOI) 10.1007/11925903_25 en_US dc.doi.uri (DOI) http://dx.doi.org/10.1007/11925903_25 en_US
