فهرست نشریات علمی دسترسی آزاد ایران

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.