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題名 多變量模糊時間數列分析與轉折區間檢測
Multivariate Fuzzy Time Series Analysis with Change Periods Detection
作者 廖俊銘
貢獻者 吳柏林
廖俊銘
關鍵詞 模糊關係
模糊馬可夫關係矩陣
多變量模糊時間數列
模糊規則庫
平均預測秩階準確度
Fuzzy relation
fuzzy markov relative matrix
multivariate fuzzy time series
fuzzy rule base
average forecasting accuracy
日期 2009
上傳時間 11-十月-2011 16:56:05 (UTC+8)
摘要 近年來,隨著科技的進步與工商業的發展,預測技術的創新與改進愈來愈受到重視,同樣地,對於預測準確度的要求也愈來愈高。尤其在經濟建設、人口政策、經營規畫、管理控制等問題上,預測更是決策過程中不可或缺的重要資訊。有鑑於此,本論文嘗試應用模糊關係方程式,提出多變量模糊時間數列建構過程及轉折區間檢測模式理論架構。另一方面,多變量模糊時間數列模式建構過程,研究者曾提出很多轉折點之偵測與檢定方法,然而在實際的例子中,時間數列之結構改變所呈現出來的是一種緩慢的改變過程,即轉折點本身就是模糊不確定。這個概念在建構不同模式分析各國經濟活動數據時更顯重要。本論文針對轉折區間之檢測提出一個完整的認定程序。多變量時間數列系統中的隸屬度函數等於在計算成果指標群時的群集中心。應用本論文提出的方法,我們以德國、法國及希臘之總體經濟指標GDP為例,考慮通貨膨脹率、GDP成長率及投資率來進行轉折區間的檢測。
In recent years, along with the technological advancement and commercial development, the creation and improvement of forecasting techniques have more and more attention. Especially at the economic developments, population policy, management planning and control, forecasting gives necessary and important information in the decision-making process. Regarding stock market as the example, these numerals of closing price are uncertain and indistinct. Again, the factors of influence on quantity are numerous, such as turnover, exchange rate etc. Therefore, if we consider merely the closing price of front day to build and forecast, we will not only misestimate the future trend, but also will cause unnecessary damage.
Owing to this reason, we propose the procedure of multivariate fuzzy time series model constructed and theory structure by fuzzy relation equation. Combining closing price with turnover, we apply our methods to build up multivariate fuzzy time series model on Taiwan Weighted Index and predict future trend while examine the predictive results with average forecasting accuracy.
A fuzzy time series is defined on averages of cumulative fuzzy entropies of the tree time series. Finally, an empirical study about change periods identification for Germany, France and Greece major macroeconomic indicators are demonstrated.
參考文獻 Balke, N. S. (1993), Detecting level shifts in time series, Journal of Business Economic Statistics, 11(1), 81-92.
Chen, S. M. (1996), Forecasting enrollments based on fuzzy time series, Fuzzy Sets and Systems, 81, 311-319.
Chiang, D., L. Chow, and Y. Wang (2000), Mining time series data by a fuzzy linguistic summary system, Fuzzy Sets and Systems, 112, 419-432.
Clymer, J., P. Corey, and J. Gardner (1992), Discrete event fuzzy airport control, IEEE Transactions on Systems, Man, and Cybernetics, 22(2), 343-351.
Cutsem, B. V., and I. Gath (1993), Detection of outliers and robust estimation using fuzzy clustering, Computational Statistics and Data Analysis, 15, 47-61.
Dubois, D. and H. Prade (1991), Fuzzy sets in approximate reasoning, Part Ⅰ: Inference with possibility distributions, Fuzzy Sets and Systems, 40, 143-202.
Graham, B. P. and R. B. Newell (1989), Fuzzy adaptive control of a first-order process, Fuzzy Sets and Systems, 31, 47-65.
Hathaway, R. J., and J. C. Bezdek (1993), Switching regression models and fuzzy clustering, IEEE Transactions of Fuzzy Systems, 1, 195-204.
Hinkley, D. V. (1971), Inference about the change point from cumulative sum test, Biometria, 26, 279-284.
Hsu, D. A. (1982), A Bayesian robust detection of shift in the risk structure of stock market returns, Journal of the American Statistical Association, 77, 29-39.
Inclan, C. & Tiao, G. C. (1994), Use of cumulative sums of squares for retrospective detection of changes of variance, Journal of the American Statistical Association, 89(427), 913-924.
Lee, Y. C., C. Hwnag, and Y. P. Shih (1994), A combined approach to fuzzy model identification. IEEE Transactions on Systems, Man, and Cybernetics, 24(5), 736-743.
Lowen, R. (1990), A fuzzy language interpolation theorem, Fuzzy Sets and Systems, 34, 33-38.
Manski, C. (1990), The use of intention data to predict behavior: a best case analysis, Journal of the American Statistical Association, 85, 934-940.
Nguyen, H. and M. Sugeno (1998), Fuzzy Modeling and Control, CRC Press.
Page, E. S. (1955), A test for change in a parameter occurring at an unknown point, Biometricka, 42, 523-527.
Park, Y. M., U. C. Moon, and K. Y. Lee (1995), A self-organizing fuzzy logic controller for dynamic systems using fuzzy auto-regressive moving average (FARMA) model, IEEE Transactions on Fuzzy Systems, 3(1), 75-82.
Romer, C., A. Kandel, and E. Backer (1995), Fuzzy partitions of the sample space and fuzzy parameter hypotheses, IEEE Transactions on Systems, Man and Cybernetics, 25(9), 1314-1321.
Ruspini, E. (1991), Approximate reasoning: past, present, future, Information Sciences, 57, 297-317.
Song, Q. and B. S. Chissom (1993a), Forecasting enrollments with fuzzy time series—Part I, Fuzzy Sets and Systems, 54, 1-9.
Song, Q. and B. S. Chissom (1993b), Fuzzy time series and its models, Fuzzy Sets and Systems, 54, 269-277.
Song, Q. and B. S. Chissom (1994), Forecasting enrollments with fuzzy time series—Part II, Fuzzy Sets and Systems, 62, 1-8.
Song, Q., R. P. Leland, and B. S. Chissom (1997) , Fuzzy stochastic fuzzy time series and its models, Fuzzy Sets and Systems, 88, 333-341.
Sugeno, M. and K. Tanaka (1991), Successive identification of a fuzzy model and its applications to prediction of a complex system, Fuzzy Sets and Systems, 42, 315-334.
Tong, R. M. (1978), Synthesis of fuzzy models for industrial processes, International Journal of General Systems, Vol.4, 143-162.
Tsay , R, S. (1991), Detecting and modeling non-linearity in univariate time series analysis, Statistica Sinica, 1(2),431-451.
Tseng, F., G. Tzeng, H. Yu, and B. Yuan (2001), Fuzzy ARIMA model for forecasting the foreign exchange market, Fuzzy Sets and Systems, 118, 9-19.
Tseng, T. and C. Klein (1992), A new algorithm for fuzzy multicriteria decision making, International Journal of Approximate Reasoning, 6, 45-66.
Werners, B. (1987), An interactive fuzzy programming system, Fuzzy Sets and Systems, 23, 131-147.
Wu, B. (1994), Identification environment and robust forecasting for nonlinear time series, Computational Economics. 7, 37-53.
Wu, W. (1986), Fuzzy reasoning and fuzzy relational equations, Fuzzy Sets and Systems, 20, 67-78.
Wu, B. and C. Sun (1996), Fuzzy statistics and computation on the lexical semantics, Language, Information and Computation (PACLIC 11), 337-346, Seoul, Korea.
Wu, B. and M. Chen (1999), Use of fuzzy statistical technique in change periods detection of nonlinear time series, Applied Mathematics and Computation, 99, 241-254.
Wu, B. and S. Hung (1999) , A fuzzy identification procedure for nonlinear time series: with example on ARCH and bilinear models, Fuzzy Sets and Systems, 108, 275-287.
Xu, C. W. and Y. Z. Lee (1987) , Fuzzy model identification and self-learning for dynamic systems, IEEE Transactions on Systems, Man, and Cybernetics, Vol. SCM-17, 683-689.
Yang, M. (1993), A Survey of Fuzzy Clustering, Mathematical and Computer Modelling, 18(11), 1-16.
Yoshinari, Y., W. Pedrycz, and K. Hirota (1993), Construction of fuzzy models through clustering techniques, Fuzzy Sets and Systems, 54, 157-165.
Zadeh, L. A. (1965), Fuzzy Sets, Information and Control, 8, 338-353.
Zimmermann, H. J. (1991), Fuzzy Set Theory and Its Applications, Boston: Kluwer Academic.
描述 碩士
國立政治大學
應用數學系數學教學碩士在職專班
94972005
98
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0094972005
資料類型 thesis
dc.contributor.advisor 吳柏林zh_TW
dc.contributor.author (作者) 廖俊銘zh_TW
dc.creator (作者) 廖俊銘zh_TW
dc.date (日期) 2009en_US
dc.date.accessioned 11-十月-2011 16:56:05 (UTC+8)-
dc.date.available 11-十月-2011 16:56:05 (UTC+8)-
dc.date.issued (上傳時間) 11-十月-2011 16:56:05 (UTC+8)-
dc.identifier (其他 識別碼) G0094972005en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/51586-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 應用數學系數學教學碩士在職專班zh_TW
dc.description (描述) 94972005zh_TW
dc.description (描述) 98zh_TW
dc.description.abstract (摘要) 近年來,隨著科技的進步與工商業的發展,預測技術的創新與改進愈來愈受到重視,同樣地,對於預測準確度的要求也愈來愈高。尤其在經濟建設、人口政策、經營規畫、管理控制等問題上,預測更是決策過程中不可或缺的重要資訊。有鑑於此,本論文嘗試應用模糊關係方程式,提出多變量模糊時間數列建構過程及轉折區間檢測模式理論架構。另一方面,多變量模糊時間數列模式建構過程,研究者曾提出很多轉折點之偵測與檢定方法,然而在實際的例子中,時間數列之結構改變所呈現出來的是一種緩慢的改變過程,即轉折點本身就是模糊不確定。這個概念在建構不同模式分析各國經濟活動數據時更顯重要。本論文針對轉折區間之檢測提出一個完整的認定程序。多變量時間數列系統中的隸屬度函數等於在計算成果指標群時的群集中心。應用本論文提出的方法,我們以德國、法國及希臘之總體經濟指標GDP為例,考慮通貨膨脹率、GDP成長率及投資率來進行轉折區間的檢測。zh_TW
dc.description.abstract (摘要) In recent years, along with the technological advancement and commercial development, the creation and improvement of forecasting techniques have more and more attention. Especially at the economic developments, population policy, management planning and control, forecasting gives necessary and important information in the decision-making process. Regarding stock market as the example, these numerals of closing price are uncertain and indistinct. Again, the factors of influence on quantity are numerous, such as turnover, exchange rate etc. Therefore, if we consider merely the closing price of front day to build and forecast, we will not only misestimate the future trend, but also will cause unnecessary damage.
Owing to this reason, we propose the procedure of multivariate fuzzy time series model constructed and theory structure by fuzzy relation equation. Combining closing price with turnover, we apply our methods to build up multivariate fuzzy time series model on Taiwan Weighted Index and predict future trend while examine the predictive results with average forecasting accuracy.
A fuzzy time series is defined on averages of cumulative fuzzy entropies of the tree time series. Finally, an empirical study about change periods identification for Germany, France and Greece major macroeconomic indicators are demonstrated.
en_US
dc.description.tableofcontents 多變量模糊時間數列分析與轉折區間檢測 1
第一章 前言 4
第二章 多變量模糊時間數列模式建構與預測 7
2.1 多變量模糊時間數列模式建構 7
2.2 如何由模糊規則庫進行屬性判別 8
2.3 多變量模糊時間數列之預測 11
2.4 平均預測秩階準確度 12
第三章 模糊決策過程 14
3.1 模糊轉折 14
3.2 群落中心 15
第四章 實證分析 19
第五章 結論 23
參考文獻 24
zh_TW
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0094972005en_US
dc.subject (關鍵詞) 模糊關係zh_TW
dc.subject (關鍵詞) 模糊馬可夫關係矩陣zh_TW
dc.subject (關鍵詞) 多變量模糊時間數列zh_TW
dc.subject (關鍵詞) 模糊規則庫zh_TW
dc.subject (關鍵詞) 平均預測秩階準確度zh_TW
dc.subject (關鍵詞) Fuzzy relationen_US
dc.subject (關鍵詞) fuzzy markov relative matrixen_US
dc.subject (關鍵詞) multivariate fuzzy time seriesen_US
dc.subject (關鍵詞) fuzzy rule baseen_US
dc.subject (關鍵詞) average forecasting accuracyen_US
dc.title (題名) 多變量模糊時間數列分析與轉折區間檢測zh_TW
dc.title (題名) Multivariate Fuzzy Time Series Analysis with Change Periods Detectionen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) Balke, N. S. (1993), Detecting level shifts in time series, Journal of Business Economic Statistics, 11(1), 81-92.zh_TW
dc.relation.reference (參考文獻) Chen, S. M. (1996), Forecasting enrollments based on fuzzy time series, Fuzzy Sets and Systems, 81, 311-319.zh_TW
dc.relation.reference (參考文獻) Chiang, D., L. Chow, and Y. Wang (2000), Mining time series data by a fuzzy linguistic summary system, Fuzzy Sets and Systems, 112, 419-432.zh_TW
dc.relation.reference (參考文獻) Clymer, J., P. Corey, and J. Gardner (1992), Discrete event fuzzy airport control, IEEE Transactions on Systems, Man, and Cybernetics, 22(2), 343-351.zh_TW
dc.relation.reference (參考文獻) Cutsem, B. V., and I. Gath (1993), Detection of outliers and robust estimation using fuzzy clustering, Computational Statistics and Data Analysis, 15, 47-61.zh_TW
dc.relation.reference (參考文獻) Dubois, D. and H. Prade (1991), Fuzzy sets in approximate reasoning, Part Ⅰ: Inference with possibility distributions, Fuzzy Sets and Systems, 40, 143-202.zh_TW
dc.relation.reference (參考文獻) Graham, B. P. and R. B. Newell (1989), Fuzzy adaptive control of a first-order process, Fuzzy Sets and Systems, 31, 47-65.zh_TW
dc.relation.reference (參考文獻) Hathaway, R. J., and J. C. Bezdek (1993), Switching regression models and fuzzy clustering, IEEE Transactions of Fuzzy Systems, 1, 195-204.zh_TW
dc.relation.reference (參考文獻) Hinkley, D. V. (1971), Inference about the change point from cumulative sum test, Biometria, 26, 279-284.zh_TW
dc.relation.reference (參考文獻) Hsu, D. A. (1982), A Bayesian robust detection of shift in the risk structure of stock market returns, Journal of the American Statistical Association, 77, 29-39.zh_TW
dc.relation.reference (參考文獻) Inclan, C. & Tiao, G. C. (1994), Use of cumulative sums of squares for retrospective detection of changes of variance, Journal of the American Statistical Association, 89(427), 913-924.zh_TW
dc.relation.reference (參考文獻) Lee, Y. C., C. Hwnag, and Y. P. Shih (1994), A combined approach to fuzzy model identification. IEEE Transactions on Systems, Man, and Cybernetics, 24(5), 736-743.zh_TW
dc.relation.reference (參考文獻) Lowen, R. (1990), A fuzzy language interpolation theorem, Fuzzy Sets and Systems, 34, 33-38.zh_TW
dc.relation.reference (參考文獻) Manski, C. (1990), The use of intention data to predict behavior: a best case analysis, Journal of the American Statistical Association, 85, 934-940.zh_TW
dc.relation.reference (參考文獻) Nguyen, H. and M. Sugeno (1998), Fuzzy Modeling and Control, CRC Press.zh_TW
dc.relation.reference (參考文獻) Page, E. S. (1955), A test for change in a parameter occurring at an unknown point, Biometricka, 42, 523-527.zh_TW
dc.relation.reference (參考文獻) Park, Y. M., U. C. Moon, and K. Y. Lee (1995), A self-organizing fuzzy logic controller for dynamic systems using fuzzy auto-regressive moving average (FARMA) model, IEEE Transactions on Fuzzy Systems, 3(1), 75-82.zh_TW
dc.relation.reference (參考文獻) Romer, C., A. Kandel, and E. Backer (1995), Fuzzy partitions of the sample space and fuzzy parameter hypotheses, IEEE Transactions on Systems, Man and Cybernetics, 25(9), 1314-1321.zh_TW
dc.relation.reference (參考文獻) Ruspini, E. (1991), Approximate reasoning: past, present, future, Information Sciences, 57, 297-317.zh_TW
dc.relation.reference (參考文獻) Song, Q. and B. S. Chissom (1993a), Forecasting enrollments with fuzzy time series—Part I, Fuzzy Sets and Systems, 54, 1-9.zh_TW
dc.relation.reference (參考文獻) Song, Q. and B. S. Chissom (1993b), Fuzzy time series and its models, Fuzzy Sets and Systems, 54, 269-277.zh_TW
dc.relation.reference (參考文獻) Song, Q. and B. S. Chissom (1994), Forecasting enrollments with fuzzy time series—Part II, Fuzzy Sets and Systems, 62, 1-8.zh_TW
dc.relation.reference (參考文獻) Song, Q., R. P. Leland, and B. S. Chissom (1997) , Fuzzy stochastic fuzzy time series and its models, Fuzzy Sets and Systems, 88, 333-341.zh_TW
dc.relation.reference (參考文獻) Sugeno, M. and K. Tanaka (1991), Successive identification of a fuzzy model and its applications to prediction of a complex system, Fuzzy Sets and Systems, 42, 315-334.zh_TW
dc.relation.reference (參考文獻) Tong, R. M. (1978), Synthesis of fuzzy models for industrial processes, International Journal of General Systems, Vol.4, 143-162.zh_TW
dc.relation.reference (參考文獻) Tsay , R, S. (1991), Detecting and modeling non-linearity in univariate time series analysis, Statistica Sinica, 1(2),431-451.zh_TW
dc.relation.reference (參考文獻) Tseng, F., G. Tzeng, H. Yu, and B. Yuan (2001), Fuzzy ARIMA model for forecasting the foreign exchange market, Fuzzy Sets and Systems, 118, 9-19.zh_TW
dc.relation.reference (參考文獻) Tseng, T. and C. Klein (1992), A new algorithm for fuzzy multicriteria decision making, International Journal of Approximate Reasoning, 6, 45-66.zh_TW
dc.relation.reference (參考文獻) Werners, B. (1987), An interactive fuzzy programming system, Fuzzy Sets and Systems, 23, 131-147.zh_TW
dc.relation.reference (參考文獻) Wu, B. (1994), Identification environment and robust forecasting for nonlinear time series, Computational Economics. 7, 37-53.zh_TW
dc.relation.reference (參考文獻) Wu, W. (1986), Fuzzy reasoning and fuzzy relational equations, Fuzzy Sets and Systems, 20, 67-78.zh_TW
dc.relation.reference (參考文獻) Wu, B. and C. Sun (1996), Fuzzy statistics and computation on the lexical semantics, Language, Information and Computation (PACLIC 11), 337-346, Seoul, Korea.zh_TW
dc.relation.reference (參考文獻) Wu, B. and M. Chen (1999), Use of fuzzy statistical technique in change periods detection of nonlinear time series, Applied Mathematics and Computation, 99, 241-254.zh_TW
dc.relation.reference (參考文獻) Wu, B. and S. Hung (1999) , A fuzzy identification procedure for nonlinear time series: with example on ARCH and bilinear models, Fuzzy Sets and Systems, 108, 275-287.zh_TW
dc.relation.reference (參考文獻) Xu, C. W. and Y. Z. Lee (1987) , Fuzzy model identification and self-learning for dynamic systems, IEEE Transactions on Systems, Man, and Cybernetics, Vol. SCM-17, 683-689.zh_TW
dc.relation.reference (參考文獻) Yang, M. (1993), A Survey of Fuzzy Clustering, Mathematical and Computer Modelling, 18(11), 1-16.zh_TW
dc.relation.reference (參考文獻) Yoshinari, Y., W. Pedrycz, and K. Hirota (1993), Construction of fuzzy models through clustering techniques, Fuzzy Sets and Systems, 54, 157-165.zh_TW
dc.relation.reference (參考文獻) Zadeh, L. A. (1965), Fuzzy Sets, Information and Control, 8, 338-353.zh_TW
dc.relation.reference (參考文獻) Zimmermann, H. J. (1991), Fuzzy Set Theory and Its Applications, Boston: Kluwer Academic.zh_TW