TREND-CYCLE ESTIMATION USING FUZZY TRANSFORM OF HIGHER DEGREE
عنوان مقاله: TREND-CYCLE ESTIMATION USING FUZZY TRANSFORM OF HIGHER DEGREE
شناسه ملی مقاله: JR_IJFS-15-7_004
منتشر شده در در سال 1397
شناسه ملی مقاله: JR_IJFS-15-7_004
منتشر شده در در سال 1397
مشخصات نویسندگان مقاله:
Michal Holcapek - Institute for Research and Applications of Fuzzy Modelling, NSC IT۴Innovations, University of Ostrava, ۳۰. dubna ۲۲, ۷۰۱ ۰۳ Ostrava ۱, Czech Republic
Linh Nguyen - Institute for Research and Applications of Fuzzy Modelling, NSC IT۴Innovations, University of Ostrava, ۳۰. dubna ۲۲, ۷۰۱ ۰۳ Ostrava ۱, Czech Republic
خلاصه مقاله:
Michal Holcapek - Institute for Research and Applications of Fuzzy Modelling, NSC IT۴Innovations, University of Ostrava, ۳۰. dubna ۲۲, ۷۰۱ ۰۳ Ostrava ۱, Czech Republic
Linh Nguyen - Institute for Research and Applications of Fuzzy Modelling, NSC IT۴Innovations, University of Ostrava, ۳۰. dubna ۲۲, ۷۰۱ ۰۳ Ostrava ۱, Czech Republic
In this paper, we provide theoretical justification for the application of higher degree fuzzy transform in time series analysis. Under the assumption that a time series can be additively decomposed into a trend-cycle, a seasonal component and a random noise, we demonstrate that the higher degree fuzzy transform technique can be used for the estimation of the trend-cycle, which is one of the basic tasks in time series analysis. We prove that high frequencies appearing in the seasonal component can be arbitrarily suppressed and that random noise, as a stationary process, can be successfully decreased using the fuzzy transform of higher degree with a reasonable adjustment of parameters of a generalized uniform fuzzy partition.
کلمات کلیدی: Fuzzy transform, Time series analysis, Seasonal component, Stationary process, Random noise, Trend-cycle estimation
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1460302/