dc.contributor.advisor | 吳柏林 | zh_TW |
dc.contributor.advisor | Wu,Berlin | en_US |
dc.contributor.author (Authors) | 游鈞毅 | zh_TW |
dc.contributor.author (Authors) | Yu,Chun Yi | en_US |
dc.creator (作者) | 游鈞毅 | zh_TW |
dc.creator (作者) | Yu,Chun Yi | en_US |
dc.date (日期) | 2009 | en_US |
dc.date.accessioned | 8-Dec-2010 11:52:51 (UTC+8) | - |
dc.date.available | 8-Dec-2010 11:52:51 (UTC+8) | - |
dc.date.issued (上傳時間) | 8-Dec-2010 11:52:51 (UTC+8) | - |
dc.identifier (Other Identifiers) | G0097751006 | en_US |
dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/49459 | - |
dc.description (描述) | 碩士 | zh_TW |
dc.description (描述) | 國立政治大學 | zh_TW |
dc.description (描述) | 應用數學研究所 | zh_TW |
dc.description (描述) | 97751006 | zh_TW |
dc.description (描述) | 98 | zh_TW |
dc.description.abstract (摘要) | 資料分類的應用在時間數列的分析與預測過程相當重要。而模糊資料近年來更受到重視,其應用的範圍包含:財金、社會、生醫、電機等各個領域。本研究欲運用模糊資料分類法,對區間時間數列的轉折偵測與模式建構做一個深入探討。主要應用平均累加模糊熵(average of the sum of fuzzy entropies), 找出其結構性改變的區間。並針對區間型時間數列進行模式建構診斷與預測。最後我們以單身人口數與失業率為實列做一個詳細的探討。結果顯示,失業率對單身人口數有顯著的影響而孤鸞年的效應並不顯著。 | zh_TW |
dc.description.abstract (摘要) | The application of data classifications in time series analysis and forecasting is rather important. The fuzzy data classification has received much attention recently. It can be applied on various fields such as finance, sociology, biomedicine, electrical engineering and so on. This study is to use the fuzzy data classification to perform an intensive research on the change periods detection and model construction of the interval time series. We use average of the sum of fuzzy entropies to find out interval of the structural changes. Focusing on the time series of intervals, we build a model and make prediction about it. At the end, based on the case study on the population of singles versus, we thoroughly discuss this topic. The result shows that the unemployment rate does significantly correlate with the population of singles, but the "widow`s year" does not . | en_US |
dc.description.tableofcontents | 第一章 前言 4第二章 研究方法 62.1 ARIMA轉換模式 62.2 模糊集合與群落隸屬度 92.3 模糊熵與區間距離 102.4 轉折區間 14第三章 實證分析 163.1資料來源 163.2 以轉換模式建構 183.3 以模糊分類法分類並建立門檻轉換模式 203.4 以模糊分類法分類模糊區間 213.5 預測結果比較與分析 22第四章 結論 25第五章 參考文獻 26 | zh_TW |
dc.format.extent | 4107235 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en_US | - |
dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0097751006 | en_US |
dc.subject (關鍵詞) | 模糊資料分類 | zh_TW |
dc.subject (關鍵詞) | 轉折區間 | zh_TW |
dc.subject (關鍵詞) | 平均累加模糊熵 | zh_TW |
dc.subject (關鍵詞) | 失業率 | zh_TW |
dc.subject (關鍵詞) | 單身人口數 | zh_TW |
dc.subject (關鍵詞) | fuzzy data classification | en_US |
dc.subject (關鍵詞) | average of the sum of fuzzy entropies | en_US |
dc.subject (關鍵詞) | change periods | en_US |
dc.subject (關鍵詞) | unemployment rate | en_US |
dc.subject (關鍵詞) | population of singles | en_US |
dc.title (題名) | 模糊資料分類與模式建構探討-以單身人口數及失業率為例 | zh_TW |
dc.title (題名) | A study on the fuzzy data classification and model construction - with case study on the population of singles versus unemployment rate | en_US |
dc.type (資料類型) | thesis | en |
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