自1991年Song提出模糊時間序列模式來對具有不確定性之時間序列進行預測,後續有許多相關的研究,且都獲致不錯的結果。 然而,在建構模糊時間序列模型時,如何有效地偵測模型的階次、定義適當的隸屬度函數的區間長度、計算模糊自相關矩陣等,一直是相關研究爭議的重點,本文將針對隸屬度函數的區間長度的比較來進行探討並提出改進之方法。 本文研究重點包括:模糊隸屬度函數的定義與範圍區間長度上的取捨,模糊自相關矩陣計算的化簡及模糊時間序列模式之建構與預測等。我們首先給定模糊時間序列模式的概念與一些重要性質。再來,藉著詳細的演算比較這些區間大小不同的模糊時間序列模型,我們確立模糊時間序列分析方法的有效性。最後,使用所建構的模糊時間序列模式對未來進行預測,以驗證所建構模糊時間序列模式的效率性與實用性。
Fuzzy time series model was proposed by Song Q. in 1991, and it can forecast data effectively. Many researches indicate this method is good for forecasting time-invariant data. Since the establishment of fuzzy time series model, several controversial issues such as how to determine the order of the model, how to define the length of interval of the fuzzy membership function and how to calculate the fuzzy auto-correlation matrix. We will discuss the improvement of the interval length of the fuzzy membership function in this thesis. This thesis is to decide the interval length of fuzzy membership function, to reduce the operation of fuzzy auto-correlation matrix, to establish the fuzzy time series model and to forecast the fuzzy time series. First, we define some important definitions of fuzzy time series. Second, we compare the different fuzzy time series model and thus claim the effectiveness for the analysis of fuzzy time series. Finally, we forecast the data with the fuzzy time series model and prove the efficiency and practicability of these models.
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