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    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/71244


    Title: Fuzzy Forecasting with DNA Computing
    Authors: 鄭至甫
    Jeng, Jyh‐Fu
    Contributors: 科管智財所
    Date: 2006
    Issue Date: 2014-11-07 16:03:05 (UTC+8)
    Abstract: 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.
    Relation: Lecture Notes in Computer Science, 4287, 324-336
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1007/11925903_25
    DOI: 10.1007/11925903_25
    Appears in Collections:[科技管理與智慧財產研究所] 期刊論文

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