| dc.contributor.advisor | 吳柏林 | zh_TW |
| dc.contributor.author (Authors) | 洪鵬凱 | zh_TW |
| dc.creator (作者) | 洪鵬凱 | zh_TW |
| dc.date (日期) | 1996 | en_US |
| dc.date.accessioned | 28-Apr-2016 09:56:15 (UTC+8) | - |
| dc.date.available | 28-Apr-2016 09:56:15 (UTC+8) | - |
| dc.date.issued (上傳時間) | 28-Apr-2016 09:56:15 (UTC+8) | - |
| dc.identifier (Other Identifiers) | B2002002531 | en_US |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/87115 | - |
| 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.abstract (摘要) | 近幾年來，非線性時間數列轉折點的研究愈來愈受到重視，學者們也提出許多關於轉折點的偵測及檢定方法。若考慮實際資料走勢轉變的情形，“轉折區間”的概念更可以解釋結構改變的現象。但文獻中對於如何找尋時間數列結構改變之轉折區間的研究並不多。本文擬以時間數列統計模式及模糊學理論的角度來研究，並結合遺傳演算的規則而提出主導模式的概念，來架構出時間數列遺傳模式，再藉由轉折區間決策法則來找出數列的轉折區間。其中，我們以統計模式為遺傳演化過程中的染色體，而以候選模式之隸屬度函數為衡量染色體適應能力的指標。最後，我們舉出臺灣股價收盤指數之實例，分別以我們所提出的方法及其他方法找出數列的轉折區間及轉折點，並做比較。 | zh_TW |
| dc.description.abstract (摘要) | For recent years, the research of change point in nonlinear time series has been considered to be more and more important. Scholars have proposed a lot of detecting and testing methods about change points.If considering the trend of real situation, the concept of change period will show the phenomena of structure change.But there are not many researches about how to find change period in time series.My paper is based on the points of time series models and fuzzy theory.Besides,it combines the rules of genetic algorithm and provides the concepts of leading model to construct time seriep genetic model and to find out change period by decision rule.ln this paper, we use time series statistical models as chromosome in procedure of genetic evolution, and we also use membership function of selected models as pereformance: index of chromosome.Finally, the empirical application about change periods and change points detecting by our method and other`s for Taiwan stock closing prices is demonstrated and make a comparision with these results. | en_US |
| dc.description.tableofcontents | 1、前言-----1 2、理論與方法-----3 2.1 遺傳演算法-----3 2.2 候選模式之隸屬度函數-----5 2.3 主導模式-----8 2.4 轉折區間的判定-----11 2.5 中心化累加平方和法-----12 3、模擬分析與比較-----14 3.1 模擬資料-----14 3.2 轉折區間的判定-----16 4、實證探討-----20 4.1 資料分析-----20 4.2 遺傳模式在轉折區間判定上的應用-----21 4.3 中心化累加平方和法的應用-----23 4.4 結果分析與比較-----25 5、結論與建議-----30 參考文獻-----31 | zh_TW |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#B2002002531 | en_US |
| dc.subject (關鍵詞) | 非線性時間數列 | zh_TW |
| dc.subject (關鍵詞) | 遺傳模式 | zh_TW |
| dc.subject (關鍵詞) | 主導模式 | zh_TW |
| dc.subject (關鍵詞) | 遺傳演算法 | zh_TW |
| dc.subject (關鍵詞) | 隸屬度函數 | zh_TW |
| dc.subject (關鍵詞) | Nonlinear time series | en_US |
| dc.subject (關鍵詞) | Genetic model | en_US |
| dc.subject (關鍵詞) | Leading model | en_US |
| dc.subject (關鍵詞) | Genetic algorithms | en_US |
| dc.subject (關鍵詞) | Membership function | en_US |
| dc.title (題名) | 遺傳模式在轉折區間判定上的應用 | zh_TW |
| dc.title (題名) | The application of genetic models in change periods detection | en_US |
| dc.type (資料類型) | thesis | en_US |
