Journal of Industrial Technology (산업기술연구)
- Volume 28 Issue B
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- Pages.101-109
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- 2008
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- 1229-9588(pISSN)
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- 1598-1371(eISSN)
Multiple Model Prediction System Based on Optimal TS Fuzzy Model and Its Applications to Time Series Forecasting
최적 TS 퍼지 모델 기반 다중 모델 예측 시스템의 구현과 시계열 예측 응용
- Published : 2008.08.31
Abstract
In general, non-stationary or chaos time series forecasting is very difficult since there exists a drift and/or nonlinearities in them. To overcome this situation, we suggest a new prediction method based on multiple model TS fuzzy predictors combined with preprocessing of time series data, where, instead of time series data, the differences of them are applied to predictors as input. In preprocessing procedure, the candidates of optimal difference interval are determined by using con-elation analysis and corresponding difference data are generated. And then, for each of them, TS fuzzy predictor is constructed by using k-means clustering algorithm and least squares method. Finally, the best predictor which minimizes the performance index is selected and it works on hereafter for prediction. Computer simulation is performed to show the effectiveness and usefulness of our method.
Keywords
- data preprocessing;
- correlation analysis;
- optimal difference interval;
- multiple model fuzzy predictor;
- model selection
- 데이터 전처리;
- 상관해석;
- 최적 차분 간격;
- 다중 모델 퍼지 예측기;
- 모델선택;