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TREND-CYCLE ESTIMATION USING FUZZY TRANSFORM OF HIGHER DEGREE.
- Source :
-
Iranian Journal of Fuzzy Systems . Oct2018, Vol. 15 Issue 7, p23-54. 32p. - Publication Year :
- 2018
-
Abstract
- Ill 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 trendcycle, 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. [ABSTRACT FROM AUTHOR]
- Subjects :
- *FUZZY algorithms
*FUZZY logic
*TIME series analysis
*NUMERICAL analysis
*ALGORITHMS
Subjects
Details
- Language :
- English
- ISSN :
- 17350654
- Volume :
- 15
- Issue :
- 7
- Database :
- Academic Search Index
- Journal :
- Iranian Journal of Fuzzy Systems
- Publication Type :
- Academic Journal
- Accession number :
- 134291815