學術產出-學位論文
| 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 | 29-四月-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,Berlin | en_US |
| dc.contributor.author (作者) | 許嘉元 | zh_TW |
| dc.contributor.author (作者) | Sheu, Chia-Yuan | en_US |
| dc.creator (作者) | 許嘉元 | zh_TW |
| dc.creator (作者) | Sheu, Chia-Yuan | en_US |
| dc.date (日期) | 1994 | en_US |
| dc.date (日期) | 1993 | en_US |
| dc.date.accessioned | 29-四月-2016 15:30:57 (UTC+8) | - |
| dc.date.available | 29-四月-2016 15:30:57 (UTC+8) | - |
| dc.date.issued (上傳時間) | 29-四月-2016 15:30:57 (UTC+8) | - |
| dc.identifier (其他 識別碼) | B2002003824 | en_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) | 81354009 | zh_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 fuzzy | en_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/#B2002003824 | en_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 model | en_US |
| dc.subject (關鍵詞) | Forecasting | en_US |
| dc.subject (關鍵詞) | Fuzzy trend | en_US |
| dc.subject (關鍵詞) | Fuzzy stationary | en_US |
| dc.subject (關鍵詞) | Fuzzy time series | en_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 Series | en_US |
| dc.type (資料類型) | thesis | en_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 |