Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 2000.11d
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- Pages.666-668
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- 2000
A Fuzzy Time-Series Prediction with Preprocessing
전처리과정을 갖는 시계열데이터의 퍼지예측
- Yoon, Sang-Hun (Department of Electrical Engineering, Kangwon National University) ;
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Lee, Chul-Hee
(Department of Electrical Engineering, Kangwon National University)
- Published : 2000.11.25
Abstract
In this paper, a fuzzy prediction method is proposed for time series data having uncertainty and non-stationary characteristics. Conventional methods, which use past data directly in prediction procedure, cannot properly handle non-stationary data whose long-term mean is floating. To cope with this problem, a data preprocessing technique utilizing the differences of original time series data is suggested. The difference sets are established from data. And the optimal difference set is selected for input of fuzzy predictor. The proposed method based the Takigi-Sugeno-Kang(TSK or TS) fuzzy rule. Computer simulations show improved results for various time series.
Keywords