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題名 遺傳演算法在非線性時間數列結構改變之分析與應用
Using Genetic Algorithms to Search for the Structure Change of Non-linear Time Series
作者 阮正治
Juan, Cheng Chi
貢獻者 吳柏林
阮正治
Juan, Cheng Chi
關鍵詞 非線性時間數列分析
門檻自迴歸模式
遺傳演算法
適應函數
Non-linear time series analysis
Threshold autoregressive models
Genetic algorithms
Fitness function
日期 1996
上傳時間 28-Apr-2016 11:48:55 (UTC+8)
摘要   近幾年來,非線性時間數列分析一直是時間數列及計量經濟學者所熱衷的研究主題之一,而非線性時間數列結構改變的研究也越來越受到重視。其中的門檻自迴歸模式,雖具有線性模式所不能配適的特性,但模式建構的問題,一直是其在發展應用上的瓶頸。本研究擬以門檻自迴歸模式建構的流程並結合遺傳演算法的最佳化搜尋技術,架構出時間數列遺傳演算法,藉此演算法則及程序,全域性地搜尋最佳的門檻自迴歸模式。
  Non-linear time series analysis is a research topic which the schalors of time series and econometrics are intent on, and the research of structure change of non-linear time series is attentive. Threshold autoregressive model (TAR model) of non-linear time series has some characters which linear model fail to fit while the problem of how to find an appropriate threshold value is still attracted many researchers attention. In this paper, we present about searching the parameters for a TAR model by genetic algorithms.
描述 碩士
國立政治大學
統計學系
82354013
資料來源 http://thesis.lib.nccu.edu.tw/record/#B2002002799
資料類型 thesis
dc.contributor.advisor 吳柏林zh_TW
dc.contributor.author (Authors) 阮正治zh_TW
dc.contributor.author (Authors) Juan, Cheng Chien_US
dc.creator (作者) 阮正治zh_TW
dc.creator (作者) Juan, Cheng Chien_US
dc.date (日期) 1996en_US
dc.date.accessioned 28-Apr-2016 11:48:55 (UTC+8)-
dc.date.available 28-Apr-2016 11:48:55 (UTC+8)-
dc.date.issued (上傳時間) 28-Apr-2016 11:48:55 (UTC+8)-
dc.identifier (Other Identifiers) B2002002799en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/87312-
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) 82354013zh_TW
dc.description.abstract (摘要)   近幾年來,非線性時間數列分析一直是時間數列及計量經濟學者所熱衷的研究主題之一,而非線性時間數列結構改變的研究也越來越受到重視。其中的門檻自迴歸模式,雖具有線性模式所不能配適的特性,但模式建構的問題,一直是其在發展應用上的瓶頸。本研究擬以門檻自迴歸模式建構的流程並結合遺傳演算法的最佳化搜尋技術,架構出時間數列遺傳演算法,藉此演算法則及程序,全域性地搜尋最佳的門檻自迴歸模式。zh_TW
dc.description.abstract (摘要)   Non-linear time series analysis is a research topic which the schalors of time series and econometrics are intent on, and the research of structure change of non-linear time series is attentive. Threshold autoregressive model (TAR model) of non-linear time series has some characters which linear model fail to fit while the problem of how to find an appropriate threshold value is still attracted many researchers attention. In this paper, we present about searching the parameters for a TAR model by genetic algorithms.en_US
dc.description.tableofcontents 謝辭
摘要
Abstract
目錄
1、前言-----1
2、門檻模式與遺傳演算法-----3
  2.1 門檻模式-----3
  2.2 門檻自迴歸模式選取的演算法則-----4
  2.3 遺傳演算法-----
  2.4 遺傳演算法的原理-----7
  2.5 遺傳演算法的特性-----12
3、時間數列遺傳演算法-----14
  3.1 搜尋最佳門檻自迴歸模式-----14
  3.2 模擬-----16
4、實證探討-----18
  4.1 資料分析-----18
  4.2 參數值範圍設定-----19
  4.3 巴結果分析與比較-----20
5、結論與建議-----27
附錄-----29
參考文獻-----33
zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#B2002002799en_US
dc.subject (關鍵詞) 非線性時間數列分析zh_TW
dc.subject (關鍵詞) 門檻自迴歸模式zh_TW
dc.subject (關鍵詞) 遺傳演算法zh_TW
dc.subject (關鍵詞) 適應函數zh_TW
dc.subject (關鍵詞) Non-linear time series analysisen_US
dc.subject (關鍵詞) Threshold autoregressive modelsen_US
dc.subject (關鍵詞) Genetic algorithmsen_US
dc.subject (關鍵詞) Fitness functionen_US
dc.title (題名) 遺傳演算法在非線性時間數列結構改變之分析與應用zh_TW
dc.title (題名) Using Genetic Algorithms to Search for the Structure Change of Non-linear Time Seriesen_US
dc.type (資料類型) thesisen_US