基於不同離散化方法之加權高階模糊時間序列模式

High-Order Weighted Fuzzy Time Series Based on Different Discretization Approach

劉仲琦(Chung-Chi Liu)

指導教授 ： 張景榮

朝陽科技大學/資訊學院/資訊管理系/碩士(2013年)

摘要

人類社會中存在許多不確定性的問題，例如經濟成長率、財務危機的預測等。自從Song 和 Chissom 兩位學者在1993年提出模糊時間序列的觀念後，許多學者先後提出不同的模式來處理這些問題。然而先前的研究在模糊化的過程中，通常僅依據主觀意見進行模糊語意的離散化，因此較不能夠客觀地反應資料集的特性。有鑑於此，這項研究的方向主要是探討在模糊時間序列中，如何客觀的決定各個區間的長度以及語意的數量。本研究提出變動長度離散化方法(Variable Length Discretization Approach, VLDA)及N分位離散化方法(N-th Quantile Discretization Approach, NQDA)[26]來結合高階加權模糊時間序列，希望這兩個模式能解決先前方法的問題。最後，為了驗證本研究提出之方法，將採用台灣證券交易所(Taiwan Stock Exchange Corporation)提供的台灣股價加權指數(Taiwan Stock Exchange Capitalization Weighted Stock Index, TAIEX)為本研究績效評估的實驗資料集，並且針對不同的績效指標納入近年其它的研究模式與本研究做比較，結果顯示本研究之預測能力有進一步的改善。此外，本研究將實際開發一套證卷市場的智慧型決策支援系統(Decision Support System, DSS)，提供投資大眾未來在面對股票市場投資時，一個有用的輔助決策支援工具。

關鍵字

決策支援系統 ； N分位離散化方法 ； 變動長度離散化方法

並列摘要

There are many uncertainty problems in the Human society, such as the forecasting of economic growth rate, financial crisis, etc. Since Song and Chissom proposed the concept of fuzzy time series in 1993, many scholars have proposed different models to deal with these problems. However, previous studies usually did not consider the transfer original data to the fuzzy linguistic value by the subjective opinions in fuzzy process, which cannot objectively show the characteristics of the data. Based on above concepts, the purpose of this study is to explore ways of determining the objective lengths of intervals and amount of linguistic in fuzzy time series. This study proposed a high-order weighted fuzzy time series model based on variable length discretization approach (VLDA) and N-th quantile discretization approach (NQDA) to make forecasts. In order to verify the proposed method, the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) from the Taiwan Stock Exchange Corporation are used in the experiment, and the experiment results are compared with other methods in with this study. The forecasting performance shows that the proposed method having better forecasting ability. An intelligent decision support system (DSS) for stock market will be developed in this study. It is supposed to be a useful decision support tools for the investor to make better trading strategies in the future stock market.

並列關鍵字

decision support system ； N-th quantile discretization approach ； variable length discretization approach

參考文獻

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