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| Title: | 非線型時間序列之動態競爭模型
Dynamic Competing Model of Non-linear Time Series |
| Authors: | 李奇穎
Lee, Chi-Ying |
| Contributors: | 吳柏林
Wu Berlin
李奇穎
Lee, Chi-Ying |
| Keywords: | 非線型時間序列
時變系統
遺傳演算法
預測
Non-linear time series
Time variant system
Genetic Algorithms
Forecasting |
| Date: | 1996 |
| Issue Date: | 2016-04-28 13:30:07 (UTC+8) |
| Abstract: | 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.
In time series analysis, we find often the trend of dynamic |
| Reference: | 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. |
| Description: | 碩士
國立政治大學
應用數學系
83751012 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#B2002002896 |
| Data Type: | thesis |
| Appears in Collections: | [應用數學系] 學位論文
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