%0 Journal Article
%T TREND-CYCLE ESTIMATION USING FUZZY TRANSFORM OF HIGHER DEGREE
%J Iranian Journal of Fuzzy Systems
%I University of Sistan and Baluchestan
%Z 1735-0654
%A Holcapek, Michal
%A Nguyen, Linh
%D 2018
%\ 10/30/2018
%V 15
%N 7
%P 23-54
%! TREND-CYCLE ESTIMATION USING FUZZY TRANSFORM OF HIGHER DEGREE
%K Fuzzy transform
%K Time series analysis
%K Seasonal component
%K Stationary process
%K Random noise
%K Trend-cycle estimation
%R 10.22111/ijfs.2018.4280
%X 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.
%U http://ijfs.usb.ac.ir/article_4280_df162dd794d144385c7904619eaad246.pdf