政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/51316

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/51316

English | 正體中文 | 简体中文 | Post-Print筆數 : 27 | Items with full text/Total items : 113324/144300 (79%)
Visitors : 51134343 Online Users : 891

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

政大典藏 > College of Science > Department of Mathematical Sciences > Theses > Item 140.119/51316

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/51316

Title:	模糊資料相關係數及在數學教育之應用 Correlation of fuzzy data and its applications in mathematical education
Authors:	林立夫
Contributors:	吳柏林林立夫
Keywords:	模糊統計區間模糊數模糊相關係數 Fuzzy statistics Interval fuzzy number Fuzzy correlation coefficient
Date:	2010
Issue Date:	2011-10-05 14:39:45 (UTC+8)
Abstract:	兩變數之間是否相關，以及相關的程度與方向是統計研究學者所關注的一項課題。傳統上使用皮爾森相關係數(Pearson’s Correlation Coefficient)來表達兩實數變數間線性關係的強度與方向。然而，對於反映人類思維不確定性的模糊資料而言，傳統的相關分析方法卻有不足與不適用之缺失。　　本論文的主要目的在於尋求一個合理、適用的區間模糊資料相關係數，提供研究者簡單且容易計算的模糊相關係數求法，用以了解區間模糊資料間的相關程度。接著利用轉換離散型模糊數成為區間模糊數的方式，處理離散型模糊資料間的相關係數。最後，以國中數學教學現場所調查的資料做實例應用。　　In statistical studies, the correlation between two variables and its strength and direction are always concerned. Traditionally, the Pearson’s Correlation Coefficient is used to convey the linear relationship between two variables. However, the traditional correlation analysis is not applicable to the fuzzy data which are able to reflect more appropriately the uncertainty of human thinking. 　　The main purpose of the study is to find a reasonable and usable correlation coefficient of interval fuzzy data which provides researchers a simple and easy way to calculate and find the fuzzy correlation coefficient. Meanwhile, it can help us understand the correlation of interval fuzzy data. Moreover, we use the process of transforming discrete fuzzy number into the interval fuzzy number to deal with the correlation coefficient of discrete fuzzy data. Finally, we utilize the data from mathematics teaching in junior high school for application.
Reference:	[1]江彥聖 (2008)。模糊相關係數及其應用。碩士論文，國立政治大學，台北市。 [2]吳柏林 (2005)。模糊統計導論：方法與應用。台北：五南。 [3]Buckley, J. J. (2003). Fuzzy Probabilities: New Approach and Applications, Physics-Verlag, Heidelberg, Germany. [4]Buckley, J. J. (2004). Fuzzy Statistics, Springer-Verlag, Heidelberg, Germany. [5]Carlsson, C., Fuller, R. (2001). On possibilistic mean value and variance of fuzzy numbers, Fuzzy Sets and Systems 122, 315-326. [6]Dubois, D. and Prade, H (1987). The mean value of a fuzzy number, Fuzzy Sets and Systems 24, 279-300. [7]Galvo, T., and Mesiar, R. (2001). Generalized Medians, Fuzzy Sets and Systems 124, 59-64. [8]Gebhardt, J., Gil, M. A., and Kruse, R. (1998). Fuzzy set-theoretic methods in statistics, in: R. Slowinski(Ed.), Handbook on Fuzzy Sets, Fuzzy Sets in Decision Anaysis, Operations Research, and Statistics, vol. 5, Kluwer Academic Publishers, New York, 311-347. [9]H. T. Nguyen and B. Wu (2006) Fundamentals of Statistics with Fuzzy Data. New York：Springer. [10]Heilpern, S. (1992). The expected value of a fuzzy number, Fuzzy Sets and Systems 47, 81-86. [11]Hung, W. L. and Wu, J. W., (2001). A note on the correlation of fuzzy numbers by Expected interval, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 9, 517-523. [12]Hung, W. L. and Wu, J. W., (2002). Correlation of fuzzy numbers by α-cut method, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 10, 725-735. [13]Korner, R. (1997). On the Variance of Fuzzy Random Variables, Fuzzy Sets and Systems Vol. 92, 83-93. [14]Liu, S. T. and Kao, C. (2002). Fuzzy measures for correlation coefficient of fuzzy numbers. Fuzzy Sets and Systems 128, 267-275 [15]Wu, H. C. (1999). Probability density functions of Fuzzy Random Variables. Fuzzy Sets and Systems Vol. 105, 139-158. [16]Zadeh, L.A., (1965). Fuzzy sets. Information and Control 8, 338-353.
Description:	碩士國立政治大學應用數學系數學教學碩士在職專班 97972014 99
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0097972014
Data Type:	thesis
Appears in Collections:	[Department of Mathematical Sciences] Theses

Files in This Item:

File	Size	Format
201401.pdf	445Kb	Adobe PDF2	1286	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