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TREND-CYCLE ESTIMATION USING FUZZY TRANSFORM OF HIGHER DEGREE | ||
| Iranian Journal of Fuzzy Systems | ||
| مقاله 4، دوره 15، شماره 7، آذر و دی 2018، صفحه 23-54 اصل مقاله (717.81 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22111/ijfs.2018.4280 | ||
| نویسندگان | ||
| Michal Holcapek* ؛ Linh Nguyen | ||
| Institute for Research and Applications of Fuzzy Modelling, NSC IT4Innovations, University of Ostrava, 30. dubna 22, 701 03 Ostrava 1, Czech Republic | ||
| چکیده | ||
| 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. | ||
| کلیدواژهها | ||
| Fuzzy transform؛ Time series analysis؛ Seasonal component؛ Stationary process؛ Random noise؛ Trend-cycle estimation | ||
| مراجع | ||
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