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  • 한국과학기술정보연구원(KISTI) 서울분원 대회의실(별관 3층)
  • 2024년 07월 03일(수) 13:30
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  • P-ISSN1226-0657
  • E-ISSN2287-6081
  • KCI

ISSN : 1226-0657

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Vol.19 No.1

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FINANCIAL TIME SERIES FORECASTING USING FUZZY REARRANGED INTERVALS

FINANCIAL TIME SERIES FORECASTING USING FUZZY REARRANGED INTERVALS

한국수학교육학회지시리즈B:순수및응용수학 / Journal of the Korean Society of Mathematical Education Series B: The Pure and Applied Mathematics, (P)1226-0657; (E)2287-6081
2012, v.19 no.1, pp.7-21
https://doi.org/10.7468/jksmeb.2012.19.1.7
Jung, Hye-Young (Department of Mathematics, Yonsei University)
Yoon, Jin-Hee (School of Economics, Yonsei University)
Choi, Seung-Hoe (School of Liveral Arts and Science, Korea Aerospace University)
Jung, Hye-Young, Yoon, Jin-Hee, & Choi, Seung-Hoe. (2012). FINANCIAL TIME SERIES FORECASTING USING FUZZY REARRANGED INTERVALS. 한국수학교육학회지시리즈B:순수및응용수학, 19(1), 7-21, https://doi.org/10.7468/jksmeb.2012.19.1.7

Abstract

The fuzzy time series is introduced by Song and Chissom([8]) to construct a pattern for time series with vague or linguistic value. Many methods using the interval and fuzzy logical relationship related with historical data have been suggested to enhance the forecasting accuracy. But they do not fully reflect the fluctuation of historical data. Therefore, we propose the interval rearranged method to reflect the fluctuation of historical data and to improve the forecasting accuracy of fuzzy time series. Using the well-known enrollment, the proposed method is discussed and the forecasting accuracy is evaluated. Empirical studies show that the proposed method in forecasting accuracy is superior to existing methods and it fully reflects the fluctuation of historical data.

keywords
fuzzy time series, forecasting, rearranged interval method, fluctuation

참고문헌

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한국수학교육학회지시리즈B:순수및응용수학

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