日本知能情報ファジィ学会 ファジィ システム シンポジウム 講演論文集
第29回ファジィシステムシンポジウム
セッションID: MC2-1
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A hybrid method for improving forecasting accuracy utilizing genetic algorithm and its application to J-REIT stock market price data
*Yasuo IshiiKazuhiro Takeyasu
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Focusing that the equation of the exponential smoothing method(ESM) is equivalent to (1,1) order ARMA model equation, a new method of the estimation of the smoothing constant in exponential smoothing method was proposed before by us which satisfies the minimum variance of forecasting error. In this paper, we utilize the above stated theoretical solution. Firstly, we estimated the ARMA model parameter and then estimate the smoothing constants. Thus the theoretical solution is derived in a simple way and it may be utilized in various fields. The new method shows that it is useful for the time series that has various trend characteristics.
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