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題名 時間數列的模糊識別
Fuzzy Identification in Time Series
作者 孟慶宇
貢獻者 吳柏林
孟慶宇
關鍵詞 模糊識別
時間數列
模糊規則庫
Fuzzy Identification
Time Series
Fuzzy Rule Bases
日期 2000
上傳時間 18-Apr-2016 16:31:58 (UTC+8)
摘要 時間數列的模式識別在近年來逐漸受到注意。因為根據時間數列所產生的走勢型態可以作為判斷事件發生與預測未來的基礎。雙線性模式是由ARMA模式所延伸，所以不易與ARMA做一區別。本文就針對這類的問題，提出解決的方法。
Identification of time series model gets more and more attention, because we can analyze the events happened and forecast what will occur in the future based on the accurate model. Bilinear time is extended by ARMA model, so it is hard to distinguish bilinear model and ARMA model. This paper focuses on this type of subject and proposes some possible way to solve.
參考文獻 吳柏林(1994)，時間數列的圖形識別與分類，國立編譯館館刊，第23卷，第2期，317-343。
     Abraham, B. and Wei, W. S. (1984). Inferences about the parameters of a time series model with changing variance. Metrika, Vol. 31, 183-194.
     Anderw A. Weiss. (1986). ARCH and bilinear time series models: comprarion and combination. Jouranl of Business & Economic Statistics, Vol. 4, No. 1, 59-70.
     Baufays, P. and Rasson, J. P. (1985). Variance Changes in autoregressive models. Time Series Analysis: Theory and Practice. 7, ed. O. D. Anderson, New York: North-Holland, 119-127.
     Bleany, M. (1990). Some comparisions of the relative power of simple tests for structure change in regression models. Journal of Forecasting, Vol. 9,437-444.
     Chow, G. C. (1960). Testing for equalitysets of coefficients in two linear regressions. Econometrica, Vol. 28,591-605.
     C. O’brien. (1987). A test for non-linearity of prediction in time series. Journal of Time Series Analysis, Vol. 8, No. 3, 313-327.
     Carla Lnclan and George C. Tiao. (1994). Use of cumulative sums of squares for retrospective detection of changes of variance. Journal of the American Statistical, Vol. 89, No. 427, 913-924.
     De Gooijer ,J. G. and K. Kumar. (1992). Some recent development in nonlinear time series modeling, testing, and forecasting. International Journal of Forecasting, 135-156.Association, Vol. 89, No. 427, 913-923.
     Granger, C.W.J. and Andersen, A. (1978). An interoduction to bilinear time series models. Vanderhoeck and Reprecht, Gottingen. Econometrica, Vol. 60, 271-2855.
     Gy. Terdik and J. Math. (1998). A new test of linearity of time series based on the bispercturm. Journal of Time Series, Vol. 19, No. 6, 737-753.
     Ploberger, W. and Kramer, W. (1992). The CUSUM-test with OLS residualsn.
     Nyblom, J. (1989). Testing for the constance of parameters over time. Journal of the American Statistical Association, Vol. 84, 223-230.
     Pentti Saikkonen and Ritva Luukkonen. (1988). Lagrange multiplier tests for testing nonlinear in time series models. Scand J Statist, Vol. 15, 55-68.
     Priestly, M.B. (1988). Non-linear and non-stationary time series analysis. Academic Press Limited.
     Subber Rao, T. and Gabr, M. M. (1984). An interoduction to Bispectral Analysis and Bilinear Time Series Models. Lecture Notes in Statistics, Springer-Verlag, London.
     Sylvia Fruhwirt-Schnatter. (1992). On statistical inference for fuzzy data with applications to descriptive statistics. Fuzzy sets and systems, Vol. 50, 143-165.
     Tasy, R. (1988). Outliers , Level Shifts, and variance change in time series. Journal of Forecasting, Vol. 7, 1-20.
     Wu, B.and Shih, N. (1992). On the indentification problem for bilinear time series models. J. Statist. Comput. Simul. Vol. 43, 129-161.
     Wu, B. and Shu-Lin Hung. (1999). A fuzzy identification procedure for nonlnear time series: With example on ARCH and bilinear model. Fuzzy Set and System, Vol. 108, 275-287.
     Wu, B. and Mei-Hui Chen. (1999). Use of fuzzy statistical technique in change periods detection of nonlinear time series. Applied Mathematics and Computation, Vol. 99, 241-254.
描述 碩士
國立政治大學
應用數學系
資料來源 http://thesis.lib.nccu.edu.tw/record/#A2002001745
資料類型 thesis
dc.contributor.advisor 吳柏林zh_TW
dc.contributor.author (Authors) 孟慶宇zh_TW
dc.creator (作者) 孟慶宇zh_TW
dc.date (日期) 2000en_US
dc.date.accessioned 18-Apr-2016 16:31:58 (UTC+8)-
dc.date.available 18-Apr-2016 16:31:58 (UTC+8)-
dc.date.issued (上傳時間) 18-Apr-2016 16:31:58 (UTC+8)-
dc.identifier (Other Identifiers) A2002001745en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/85503-
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zh_TW
dc.description.abstract (摘要) 時間數列的模式識別在近年來逐漸受到注意。因為根據時間數列所產生的走勢型態可以作為判斷事件發生與預測未來的基礎。雙線性模式是由ARMA模式所延伸，所以不易與ARMA做一區別。本文就針對這類的問題，提出解決的方法。zh_TW
dc.description.abstract (摘要) Identification of time series model gets more and more attention, because we can analyze the events happened and forecast what will occur in the future based on the accurate model. Bilinear time is extended by ARMA model, so it is hard to distinguish bilinear model and ARMA model. This paper focuses on this type of subject and proposes some possible way to solve.en_US
dc.description.tableofcontents 封面頁
     證明書
     致謝詞
     論文摘要
     目錄
     1. 前言
     2. 模糊識別
     2.1 知識庫
     2.2 特徵擷取
     2.3 模糊規則庫
     2.4 識別過程
     3. 模擬
     4. 實證分析
     5. 結論
     參考文獻		zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#A2002001745en_US
dc.subject (關鍵詞) 模糊識別zh_TW
dc.subject (關鍵詞) 時間數列zh_TW
dc.subject (關鍵詞) 模糊規則庫zh_TW
dc.subject (關鍵詞) Fuzzy Identificationen_US
dc.subject (關鍵詞) Time Seriesen_US
dc.subject (關鍵詞) Fuzzy Rule Basesen_US
dc.title (題名) 時間數列的模糊識別zh_TW
dc.title (題名) Fuzzy Identification in Time Seriesen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 吳柏林(1994)，時間數列的圖形識別與分類，國立編譯館館刊，第23卷，第2期，317-343。
     Abraham, B. and Wei, W. S. (1984). Inferences about the parameters of a time series model with changing variance. Metrika, Vol. 31, 183-194.
     Anderw A. Weiss. (1986). ARCH and bilinear time series models: comprarion and combination. Jouranl of Business & Economic Statistics, Vol. 4, No. 1, 59-70.
     Baufays, P. and Rasson, J. P. (1985). Variance Changes in autoregressive models. Time Series Analysis: Theory and Practice. 7, ed. O. D. Anderson, New York: North-Holland, 119-127.
     Bleany, M. (1990). Some comparisions of the relative power of simple tests for structure change in regression models. Journal of Forecasting, Vol. 9,437-444.
     Chow, G. C. (1960). Testing for equalitysets of coefficients in two linear regressions. Econometrica, Vol. 28,591-605.
     C. O’brien. (1987). A test for non-linearity of prediction in time series. Journal of Time Series Analysis, Vol. 8, No. 3, 313-327.
     Carla Lnclan and George C. Tiao. (1994). Use of cumulative sums of squares for retrospective detection of changes of variance. Journal of the American Statistical, Vol. 89, No. 427, 913-924.
     De Gooijer ,J. G. and K. Kumar. (1992). Some recent development in nonlinear time series modeling, testing, and forecasting. International Journal of Forecasting, 135-156.Association, Vol. 89, No. 427, 913-923.
     Granger, C.W.J. and Andersen, A. (1978). An interoduction to bilinear time series models. Vanderhoeck and Reprecht, Gottingen. Econometrica, Vol. 60, 271-2855.
     Gy. Terdik and J. Math. (1998). A new test of linearity of time series based on the bispercturm. Journal of Time Series, Vol. 19, No. 6, 737-753.
     Ploberger, W. and Kramer, W. (1992). The CUSUM-test with OLS residualsn.
     Nyblom, J. (1989). Testing for the constance of parameters over time. Journal of the American Statistical Association, Vol. 84, 223-230.
     Pentti Saikkonen and Ritva Luukkonen. (1988). Lagrange multiplier tests for testing nonlinear in time series models. Scand J Statist, Vol. 15, 55-68.
     Priestly, M.B. (1988). Non-linear and non-stationary time series analysis. Academic Press Limited.
     Subber Rao, T. and Gabr, M. M. (1984). An interoduction to Bispectral Analysis and Bilinear Time Series Models. Lecture Notes in Statistics, Springer-Verlag, London.
     Sylvia Fruhwirt-Schnatter. (1992). On statistical inference for fuzzy data with applications to descriptive statistics. Fuzzy sets and systems, Vol. 50, 143-165.
     Tasy, R. (1988). Outliers , Level Shifts, and variance change in time series. Journal of Forecasting, Vol. 7, 1-20.
     Wu, B.and Shih, N. (1992). On the indentification problem for bilinear time series models. J. Statist. Comput. Simul. Vol. 43, 129-161.
     Wu, B. and Shu-Lin Hung. (1999). A fuzzy identification procedure for nonlnear time series: With example on ARCH and bilinear model. Fuzzy Set and System, Vol. 108, 275-287.
     Wu, B. and Mei-Hui Chen. (1999). Use of fuzzy statistical technique in change periods detection of nonlinear time series. Applied Mathematics and Computation, Vol. 99, 241-254.		zh_TW