政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/49459

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/49459

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政大典藏 > College of Science > Department of Mathematical Sciences > Theses > Item 140.119/49459

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/49459

Title:	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 A study on the fuzzy data classification and model construction - with case study on the population of singles versus unemployment rate
Authors:	游鈞毅 Yu,Chun Yi
Contributors:	吳柏林 Wu,Berlin 游鈞毅 Yu,Chun Yi
Keywords:	模糊資料分類轉折區間平均累加模糊熵失業率單身人口數 fuzzy data classification average of the sum of fuzzy entropies change periods unemployment rate population of singles
Date:	2009
Issue Date:	2010-12-08 11:52:51 (UTC+8)
Abstract:	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。 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 .
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Description:	碩士國立政治大學應用數學研究所 97751006 98
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0097751006
Data Type:	thesis
Appears in Collections:	[Department of Mathematical Sciences] Theses

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