政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/32575

English | 正體中文 | 简体中文 | Post-Print筆數 : 27 | Items with full text/Total items : 113318/144297 (79%)
Visitors : 51085319 Online Users : 929

RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.

Scope

please add "double quotation mark" for query phrases to get precise results

please goto advance search for comprehansive author search

Adv. Search

Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer

Goto mobile version

政大機構典藏 > 理學院 > 應用數學系 > 學位論文 > Item 140.119/32575

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/32575

Title:	模糊線性迴歸之研究
Authors:	趙家慶
Contributors:	宋傳欽趙家慶
Keywords:	模糊線性迴歸具影響力觀察值離群值雙重模糊線性迴歸模型隸屬度函數 fuzzy linear regression influence observation outlier doubly fuzzy linear regression membership function
Date:	2005
Issue Date:	2009-09-17 13:46:45 (UTC+8)
Abstract:	使用傳統迴歸的方式對未知事物做預測，往往不能夠精準的做出結論，縱使在相同的條件下實際去操作，也很難得到相同的結果，因此模糊數概念的建立，並運用在迴歸分析上更能有效描述預測結果的不確定性。然而模糊線性迴歸(Fuzzy Linear Regression)在利用最小平方法處理問題時，往往過於著重在模糊區間的中心與分展度上，而忽略了描述資料的模糊性，使得隸屬度函數(membership function)的功能受到相當大的限制。本文在D`Urso和Gastaldi(2000)所提出的雙重模糊線性迴歸(doubly fuzzy linear regression)模型架構下，利用Yang和Ko(1996)在LR空間下所定義模糊數間的距離公式，導出能反映隸屬度函數的最小平方估計，並引進一些傳統迴歸中常用來偵測離群值(outlier)與具影響力觀察值(influence observation)的概念與技巧，應用在模糊線性迴歸資料的偵測上。
Reference:	[1]Draper, N. R. and Smith, H., (1980). Applied Regression Analysis,Wiley, New York. [2]D`Urso, P. and Gastaldi, T., (2000). A least-squares approach to fuzzy linear regression analysis. 34, 427-440. [3]D`Urso, P., (2003). Linear regression analysis for fuzzy/crisp input and fuzzy/crisp output data. 42,47-72. [4]Tanaka, H., (1987). Fuzzy data analysis by possibilistic linear models. [5]Tanaka, H., Uejima, S., Asai, K., (1982). Fuzzy limear regression model.903-907. [6]Xu, R. and Li, C., (2001). Multidimensional least-squares fitting with a fuzzy model.215-223. [7]Yang, M. S. and Ko, C. H., (1996). On a class of $c$-numberrs clustering procedures for fuzzy data.84,49-60. [8]Yang, M. S. and Liu, H. H., (2003). Fuzzy least-squares algorithms for interactive fuzzy linear regression modles.135, 305-316. [9]Yang, M. S. and Liu, H. H., (2005). A new statistic for influence in linear regression.47, 305-316 [10]Zimmermann, H. J., (1991). Fuzzy Set Theory and its Applications,Kluwer,Dordrecht. [11]吳柏林(2005)：模糊統計導論方法與應用。台北，五南圖書出版社。
Description:	碩士國立政治大學應用數學研究所 93751003 94
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0093751003
Data Type:	thesis
Appears in Collections:	[應用數學系] 學位論文

Files in This Item:

File	Description	Size	Format
75100301.pdf		69Kb	Adobe PDF2	681	View/Open
75100302.pdf		306Kb	Adobe PDF2	664	View/Open
75100303.pdf		469Kb	Adobe PDF2	709	View/Open
75100304.pdf		609Kb	Adobe PDF2	803	View/Open
75100305.pdf		645Kb	Adobe PDF2	780	View/Open
75100306.pdf		602Kb	Adobe PDF2	728	View/Open
75100307.pdf		497Kb	Adobe PDF2	1154	View/Open
75100308.pdf		552Kb	Adobe PDF2	863	View/Open
75100309.pdf		447Kb	Adobe PDF2	1265	View/Open
75100310.pdf		829Kb	Adobe PDF2	784	View/Open

All items in 政大典藏 are protected by copyright, with all rights reserved.

社群 sharing

著作權政策宣告 Copyright Announcement

1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.

DSpace Software Copyright © 2002-2004 MIT & Hewlett-Packard / Enhanced by NTU Library IR team Copyright © - Feedback