| dc.contributor.advisor | 吳柏林 | zh_TW |
| dc.contributor.advisor | Wu Berlin | en_US |
| dc.contributor.author (Authors) | 李奇穎 | zh_TW |
| dc.contributor.author (Authors) | Lee, Chi-Ying | en_US |
| dc.creator (作者) | 李奇穎 | zh_TW |
| dc.creator (作者) | Lee, Chi-Ying | en_US |
| dc.date (日期) | 1996 | en_US |
| dc.date.accessioned | 28-Apr-2016 13:30:07 (UTC+8) | - |
| dc.date.available | 28-Apr-2016 13:30:07 (UTC+8) | - |
| dc.date.issued (上傳時間) | 28-Apr-2016 13:30:07 (UTC+8) | - |
| dc.identifier (Other Identifiers) | B2002002896 | en_US |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/87371 | - |
| 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 (描述) | 83751012 | zh_TW |
| dc.description.abstract (摘要) | 時間序列分析發展至今,常常發現動態資料的走勢,隨著時間過程而演變.所以傳統的模式配適常無法得到很好的解釋,因此許多學者提出不同的模型建構方法.但是對於初始模式族的選擇,卻充滿相當的主觀與經驗認定成份.本文針對時變型時間序列分析,考慮利用知識庫,由模式庫來判斷初始模式.再藉由遺傳演算法的觀念,建立模式參數的遺傳關係.我們把這種遺傳演算法,稱之為時變遺傳演算法.針對台灣省國中數學教師人數,分別以時變遺傳演算法,狀態空間,與單變量ARIMA來建構模式,並作比較.比較結果發現,時變遺傳演算法較能掌握資料反轉的趨勢,且預測值增加較為平緩.因此時變遺傳演算法在模式建構上將是個不錯的選擇. | zh_TW |
| dc.description.abstract (摘要) | In time series analysis, we find often the trend of dynamic | en_US |
| dc.description.tableofcontents | 一.前言..........1 二.遺傳演算法之理論架構..........3 2.1知識庫的學習方法..........3 2.2遺傳演算法(GENETIC ALGORITHM)..........4 三.非線型時間序列動態競爭模型之實證應用..........9 3.1資料分析..........9 3.2時變遺傳演算法所建構之模型..........11 3.3狀態空間所建構之模型..........13 3.4單變量時間序列所建構之模型..........16 四.各種方法之應用比較..........18 4.1方法論之比較..........18 4.2實證應用之比較..........19 五.結論..........21 參考文獻..........22 附錄..........24 | zh_TW |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#B2002002896 | en_US |
| dc.subject (關鍵詞) | 非線型時間序列 | zh_TW |
| dc.subject (關鍵詞) | 時變系統 | zh_TW |
| dc.subject (關鍵詞) | 遺傳演算法 | zh_TW |
| dc.subject (關鍵詞) | 預測 | zh_TW |
| dc.subject (關鍵詞) | Non-linear time series | en_US |
| dc.subject (關鍵詞) | Time variant system | en_US |
| dc.subject (關鍵詞) | Genetic Algorithms | en_US |
| dc.subject (關鍵詞) | Forecasting | en_US |
| dc.title (題名) | 非線型時間序列之動態競爭模型 | zh_TW |
| dc.title (題名) | Dynamic Competing Model of Non-linear Time Series | en_US |
| dc.type (資料類型) | thesis | en_US |
| dc.relation.reference (參考文獻) | 湯振鶴(1 991). 台灣區國民中學八十至八十六學年度教師需求量之推估研究報告.台灣省教育廳﹒台北市教育局、高雄市教育局合辦台中市大德國中承辦 馬信行(1987) 我國各級學校未來學生數之預測，政大學報第56期，117-147 馬信行(1 992) 我國各級學校師資之預測 政大學報第65期 63-80 詐瑞雯、吳柏林(1 994). 台灣地區國中教師數預測模式 教育與心理研究第17期29-44. 台灣省政府教育廳(1971-1994) 台灣省教育統計年報 Andel, J. ( 1993 ) . A Time Series Model with Suddenly Changing Paramenters. Journal of Time Series Analysys. vol. 14 No.2. 111-123. Akaike, H. (1974). A New Look at The Statistical Model Identtification. IEEE Transactions on Automatic Control. AC-19. 716-723. Box, G. E . P. and Jenkins, G. M. (1976). Time Series Analysis: Forecasting and Control. Holden-Day, San Fancisco. Giordana, A., Saitta, L., Campidogio, M. E. and Bello, G. L. (1993). Learning Relations Using Genetic Algorithms. Advances in Artifical Intelligence. 218-229. Goldberg, D. E. (1989). Genetic Algorithms: In Search, Optimization, and Machine Learning. Addison-Wesley Publishing Company. Inclan, C. and Tiao, G. C. (1994). Use of Cumulative Sum of Squares for Retrospective Detection of changes of Variance. Journal of the American Statistical Association. 913-923. Koza, 1. R. (1994) . Genetic Programming 11 : Automatic Discovery of Reusable Programs. N1IT Press, 1994. Laurence, D. (1992). Genetic Algorithms and Financial Applications. Neural ` Genetic and Fuzzy Systems for Chaotic Financiallvfarkets. 133-147. John Wiley and Sons Inc. Odetayo, M. O. (1995). Knowledge Acquisition and Adaptation: A Genetic Approach. Expert Systems. vol.l2, No.1. 3-13. Parzen, E. (1977). Multiple Time Series Modeling : Detennining The Order of Approximating Autoregressive Schemes. Multivariate Analysis IV 283-295 . Schwartz, G. (1978). Estimating The Dimension of A Model. Ann.Statist, 6 . 461-464. Shumway, R. H. and Stoffer, D. S. (1991). Dynamjc Linear Models With Switching. Journal ojthe American Statistical Association. 763-769. Wei, W. \\V. S. (1990). Time Series Analysis: Univariate and Multivariate Methods. Addision-Wesley Inc. Zurada,1. M. ( 1992). Introduction to Artifical Neural System. 56-58. West Publishing Company. | zh_TW |
