A Revised Fuzzy Time Series Method

Abstract:

In this paper,we presents two methods to forecast secular trend and seasonal variation time series problems respectively. The revised fuzzy time series method uses Song and Chrisom’s first-order time-invariant model to predict such linguistic historical data problems. This method obtains a better average error than the error in Song and Chrisom’s method. The method using fuzzy regression theory solves the shortcoming that fuzzy time series method could not work in dealing with seasonal variation time series problems.

• Periodical: Advanced Materials Research (Volumes 171-172)
• Pages: 140-143
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.171-172.140
• Online since: December 2010
• Authors: Yan Hua Yu, Li Xia Song
• Keywords: Fuzzification, Fuzzy Time Series, Linguistic Values

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