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題名 時間數列的模糊分析和預測
Fuzzy Analysis and Forecasting in Time Series
作者 許嘉元
Sheu, Chia-Yuan
貢獻者 吳柏林
Wu,Berlin
許嘉元
Sheu, Chia-Yuan
關鍵詞 模糊自我迴歸模式
預測
模糊趨勢
模糊穩定
中央政府總預算
匯率
Fuzzy autoregressive model
Forecasting
Fuzzy trend
Fuzzy stationary
Fuzzy time series
日期 1994
1993
上傳時間 29-Apr-2016 15:30:57 (UTC+8)
摘要 動態資料往往隨著時間區間取法或測量工具的不同而有差異,此種不確定的特質我們稱為模糊性。但是傳統的時間數列仍是以確定的觀察值來記錄具有模糊性的動態資料。為了更完整的表示一個動態過程,我們考慮模糊時間數列(fuzzy time series)以具有不確定性的模糊集合來取代明確的數值,保持原來的模糊性。
Representations of dynamic data are always different as the time interval or measuring tool change. We call these characteristics of uncertainty fuzziness. But traditional time series use crisp observations to record a fuzzy dynamic process. To completely represent, we consider fuzzy time series replacing the crisp numbers with fuzzy sets and preserve original fuzziness. In this paper, the fuzzy
參考文獻 Alho, J. M. (1992). Estimating the Strength of Expert Judgement: The case of US Mortality Forecasts, Journal of Forecasting, 11, 157-167.
Ascher, W. (1978) . Forecasting: An Appraisal for Policy Makers and Planners, Baltimore, MD: John Hopkins University Press.
Box, G. E. P. and Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. San Francisco, CA, Holden-Day.
Baghestani, H . and McNown, R. (1992). Forecasting the Federal Budget with Time Series Models, Journal of Forecasting, 11, 127-139.
Cox, D. R. and Stuart, A. (1955). Some Quick Tests for Trend in Location and Dispersion, Biometrika, 42, 80-95.
Funke, M. (1992). Time Series Forecasting of the German Unemployment Rate, Journal of Forecasting , 11, 127-139.
Haines, L. M. , Munoz, W. P. and VanGelderen, C. J. (1989). ARIMA Modeling of Birth Data, Journal of Applied Statistics, 16(1), 55-67.
McNown, R. F. (1986). On the Uses of Econometric Models: A Guide for Policy Makers, Policy Science , 11.9, 359-380.
Nassiuma, D. (1993) . Non-stationary Autoregressive Moving-average Processes with Infinit Variance, Journal of Time series analysis, 14(3), 297-304.
Priestley, M. B. (1988). Non-linear and Non-stationary Time Series Analysis. Academic Press, London.
Rao, S., Kanade, A., Joshi, S. and Paranjape, S. (1991). Application of Time Series Models to Detect Regulatory Patterns in Nitrogen Output of Adult
Rats, Journal of Applied Statistics, 18(2), 215-232.
Song, Q. and Chissom, B. S. (1993a) . Fuzzy Time Series and its Models, Fuzzy Sets and Systems, 54, 267-277.
Song, Q. and Chissom, B. S. (1993b). Forecasting Enrollments With Fuzzy Time Series-Part I, Fuzzy Sets and Systems, 54, 1-9.
Tong, H. (1990). Non-linear Time Series: A Dynamical System Approach, Oxford University press, London.
Torres, G. L., Silva, L. E. , Valiquette, B., Greiss, H. and Mukhedkar, D. (1992). A Fuzzy Knowledge-based System for Bus Load Forecasting, IEEE, International Conference on Fuzzy Systems, 1211-1218.
Tsay, R. S. (1991). Detecting and Modeling Nonlinearity in Univariate Time Series Analysis, Statistica Sinica, 1(2), 431-451.
Turner, D. S. (1990). The Role of Judgement in Macroeconomic Forecasting, Journal of Forecasting, 9, 315-345.
Vu, B. and Shih, N. H. (1992). On the Identification Problem for Bilinear Time Series Models, Journal of Statistical Computation and Simulation, 43, 129-161.
Zadeh, L. A. (1965) . Fuzzy Sets, Information and Control, 8, 338-353.
Zimmermann, H. J. (1991). Fuzzy Set Theory and its Applications, Boston: Kluwer Academi Publishers.
描述 碩士
國立政治大學
統計學系
81354009
資料來源 http://thesis.lib.nccu.edu.tw/record/#B2002003824
資料類型 thesis
dc.contributor.advisor 吳柏林zh_TW
dc.contributor.advisor Wu,Berlinen_US
dc.contributor.author (Authors) 許嘉元zh_TW
dc.contributor.author (Authors) Sheu, Chia-Yuanen_US
dc.creator (作者) 許嘉元zh_TW
dc.creator (作者) Sheu, Chia-Yuanen_US
dc.date (日期) 1994en_US
dc.date (日期) 1993en_US
dc.date.accessioned 29-Apr-2016 15:30:57 (UTC+8)-
dc.date.available 29-Apr-2016 15:30:57 (UTC+8)-
dc.date.issued (上傳時間) 29-Apr-2016 15:30:57 (UTC+8)-
dc.identifier (Other Identifiers) B2002003824en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/88356-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 統計學系zh_TW
dc.description (描述) 81354009zh_TW
dc.description.abstract (摘要) 動態資料往往隨著時間區間取法或測量工具的不同而有差異,此種不確定的特質我們稱為模糊性。但是傳統的時間數列仍是以確定的觀察值來記錄具有模糊性的動態資料。為了更完整的表示一個動態過程,我們考慮模糊時間數列(fuzzy time series)以具有不確定性的模糊集合來取代明確的數值,保持原來的模糊性。zh_TW
dc.description.abstract (摘要) Representations of dynamic data are always different as the time interval or measuring tool change. We call these characteristics of uncertainty fuzziness. But traditional time series use crisp observations to record a fuzzy dynamic process. To completely represent, we consider fuzzy time series replacing the crisp numbers with fuzzy sets and preserve original fuzziness. In this paper, the fuzzyen_US
dc.description.tableofcontents 1. Introduction 1
2.Fuzzy representation of time series 4
2.1Fuzzy time series and FAR(p) model 4
2.2Analysis of fuzzy trend 6
2.3Analysis of fuzzy stationary 10
2.4Procedures for FAR(p) model construction 15
3.Fuzzy forecasting for Central government expenditure 17
3.1Fuzzification and fuzzy trend checking 17
3.2Model construction and forecasting 21
3.3Comparison with ARMA model 24
4.Fuzzy forecasting of exchange rates 27
4.1Fuzzification 27
4.2Modeling and forecasting 26
4.3Using more historical data 32
5.Conclusion 36
Reference 37		zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#B2002003824en_US
dc.subject (關鍵詞) 模糊自我迴歸模式zh_TW
dc.subject (關鍵詞) 預測zh_TW
dc.subject (關鍵詞) 模糊趨勢zh_TW
dc.subject (關鍵詞) 模糊穩定zh_TW
dc.subject (關鍵詞) 中央政府總預算zh_TW
dc.subject (關鍵詞) 匯率zh_TW
dc.subject (關鍵詞) Fuzzy autoregressive modelen_US
dc.subject (關鍵詞) Forecastingen_US
dc.subject (關鍵詞) Fuzzy trenden_US
dc.subject (關鍵詞) Fuzzy stationaryen_US
dc.subject (關鍵詞) Fuzzy time seriesen_US
dc.title (題名) 時間數列的模糊分析和預測zh_TW
dc.title (題名) Fuzzy Analysis and Forecasting in Time Seriesen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Alho, J. M. (1992). Estimating the Strength of Expert Judgement: The case of US Mortality Forecasts, Journal of Forecasting, 11, 157-167.
Ascher, W. (1978) . Forecasting: An Appraisal for Policy Makers and Planners, Baltimore, MD: John Hopkins University Press.
Box, G. E. P. and Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. San Francisco, CA, Holden-Day.
Baghestani, H . and McNown, R. (1992). Forecasting the Federal Budget with Time Series Models, Journal of Forecasting, 11, 127-139.
Cox, D. R. and Stuart, A. (1955). Some Quick Tests for Trend in Location and Dispersion, Biometrika, 42, 80-95.
Funke, M. (1992). Time Series Forecasting of the German Unemployment Rate, Journal of Forecasting , 11, 127-139.
Haines, L. M. , Munoz, W. P. and VanGelderen, C. J. (1989). ARIMA Modeling of Birth Data, Journal of Applied Statistics, 16(1), 55-67.
McNown, R. F. (1986). On the Uses of Econometric Models: A Guide for Policy Makers, Policy Science , 11.9, 359-380.
Nassiuma, D. (1993) . Non-stationary Autoregressive Moving-average Processes with Infinit Variance, Journal of Time series analysis, 14(3), 297-304.
Priestley, M. B. (1988). Non-linear and Non-stationary Time Series Analysis. Academic Press, London.
Rao, S., Kanade, A., Joshi, S. and Paranjape, S. (1991). Application of Time Series Models to Detect Regulatory Patterns in Nitrogen Output of Adult
Rats, Journal of Applied Statistics, 18(2), 215-232.
Song, Q. and Chissom, B. S. (1993a) . Fuzzy Time Series and its Models, Fuzzy Sets and Systems, 54, 267-277.
Song, Q. and Chissom, B. S. (1993b). Forecasting Enrollments With Fuzzy Time Series-Part I, Fuzzy Sets and Systems, 54, 1-9.
Tong, H. (1990). Non-linear Time Series: A Dynamical System Approach, Oxford University press, London.
Torres, G. L., Silva, L. E. , Valiquette, B., Greiss, H. and Mukhedkar, D. (1992). A Fuzzy Knowledge-based System for Bus Load Forecasting, IEEE, International Conference on Fuzzy Systems, 1211-1218.
Tsay, R. S. (1991). Detecting and Modeling Nonlinearity in Univariate Time Series Analysis, Statistica Sinica, 1(2), 431-451.
Turner, D. S. (1990). The Role of Judgement in Macroeconomic Forecasting, Journal of Forecasting, 9, 315-345.
Vu, B. and Shih, N. H. (1992). On the Identification Problem for Bilinear Time Series Models, Journal of Statistical Computation and Simulation, 43, 129-161.
Zadeh, L. A. (1965) . Fuzzy Sets, Information and Control, 8, 338-353.
Zimmermann, H. J. (1991). Fuzzy Set Theory and its Applications, Boston: Kluwer Academi Publishers.		zh_TW