基於季節性與混沌現象之分離性建構時間序列預測系統方法類型之研究

Constructing Time Series Forecasting System Type Methods Based on the Separability of Seasonal and Chaotic Phenomena

10.29893/NCUTMAN.201811.0022

張炳騰(Ping-Teng Chang)；曾柏健(Bo-Jian Zeng)；陳晉維(Chin-Wei Chen)

迴歸分析 ； 季節性預測 ； 類神經網路 ； 混沌現象 ； 模糊現象 ； Chaos Phenomenon ； Seasonal Variation ； Fuzzy Set ； Intuitionistic Fuzzy Set ； Artificial Neural Network

管理學術研討會

第十六屆（2018 / 11 / 01）

121 - 132

繁體中文

混沌是一種非線性但隱含規則的系統，掌握此特性是預測模式值得探討的方向。本研究除了納入上述掌握混沌變動性降低誤差的相關研究外，亦將探討另一造成預測結果失真的變動因子：季節性變動。本研究依據混沌現象與季節性兩個變動因子有其可分離性與不可分離性差別，提出三類型資料處理方法預測系統，此三類型資料處理方法將各別應用和研究多個預測方法。在預測方法中，本研究除考慮模糊不確定環境下模糊集合概念和預測方法進而提出非模糊與模糊預測系統外，更探討基於模糊理論衍生的直覺模糊集合概念，使資料的表達更貼近實際問題。同時並將探討不同領域問題資料（如交通流量、原料產量、電力負載等）做為預測模式之驗證。研究結果顯示，經季節性與混沌處理並結合模糊與直覺模糊理論的預測方法，更能貼近實際的預測結果；在長期預測結果中，模糊類神經方法的預測結果能掌握資料的長期趨勢，代表本研究方法能克服過往研究中時間序列的預測周期過長，導致預測結果失真的問題。

Chaos is a non-linear but implied rule system and it is worth exploring in the development of prediction models. In addition to incorporating the above discussion into the distortion of predictive results caused by chaotic phenomena, and then analyzing the variability and reducing the error related research, this study will also explore another variation factor that distort the prediction results: Seasonal variation. In the forecasting system proposed in this study, the data processing methods will be divided into three major types by the separability and inseparability of the seasonal variations of data. In the prediction method, this study not only considers fuzzy set concepts and prediction methods under fuzzy and uncertain environments, proposing non-fuzzy and fuzzy prediction systems, but also discusses the concept of intuitionistic fuzzy sets derived from fuzzy theory and makes the expression of data closer to practical problems. At the same time, this study will also examine the data of different areas (such as traffic flow, raw material production, electric power load, birth number, air pollution index, etc.) as a verification model. The research results show that the prediction methods based on fuzzy and intuitionistic fuzzy theory combined with seasonal and chaotic processing can be closer to the actual prediction results than the traditional methods. In the long-term prediction results, the prediction results of fuzzy neural methods can grasp the trend in long-term data, which represents the method of this study, can overcome the problem that if the prediction period of the time series prediction method in past research is too long, it will lead to distortion of the prediction result.