Publications-Books & Chapters in Books

Article View/Open

Publication Export

Google ScholarTM

NCCU Library

Citation Infomation

Related Publications in TAIR

題名 Correlation Evaluation with Fuzzy Data and its Application in the Management Science
作者 吳柏林
Wu, Berlin;Sha, Wei-Shun;Chen, Juei-Chao
貢獻者 應數系
日期 2015-01
上傳時間 16-Mar-2015 15:56:48 (UTC+8)
摘要 How to evaluate an appropriate correlation with fuzzy data is an important topic in the educational and psychological measurement. Especially when the data illustrate uncertain, inconsistent and incomplete type, fuzzy statistical method has some promising features that help resolving the unclear thinking in human logic and recognition. Traditionally, we use Pearson’s Correlation Coefficient to measure the correlation between data with real value. However, when the data are composed of fuzzy numbers, it is not feasible to use such a traditional approach to determine the fuzzy correlation coefficient. This study proposes the calculation of fuzzy correlation with three types of fuzzy data: interval, triangular and trapezoidal. Empirical studies are used to illustrate the application for evaluating fuzzy correlations. More related practical phenomena can be explained by this appropriate definition of fuzzy correlation.
關聯 Econometrics of Risk, Springer Verlag, pp.273-285
資料類型 book/chapter
DOI http://dx.doi.org/10.1007/978-3-319-13449-9_19
dc.contributor 應數系-
dc.creator (作者) 吳柏林-
dc.creator (作者) Wu, Berlin;Sha, Wei-Shun;Chen, Juei-Chao-
dc.date (日期) 2015-01-
dc.date.accessioned 16-Mar-2015 15:56:48 (UTC+8)-
dc.date.available 16-Mar-2015 15:56:48 (UTC+8)-
dc.date.issued (上傳時間) 16-Mar-2015 15:56:48 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/73870-
dc.description.abstract (摘要) How to evaluate an appropriate correlation with fuzzy data is an important topic in the educational and psychological measurement. Especially when the data illustrate uncertain, inconsistent and incomplete type, fuzzy statistical method has some promising features that help resolving the unclear thinking in human logic and recognition. Traditionally, we use Pearson’s Correlation Coefficient to measure the correlation between data with real value. However, when the data are composed of fuzzy numbers, it is not feasible to use such a traditional approach to determine the fuzzy correlation coefficient. This study proposes the calculation of fuzzy correlation with three types of fuzzy data: interval, triangular and trapezoidal. Empirical studies are used to illustrate the application for evaluating fuzzy correlations. More related practical phenomena can be explained by this appropriate definition of fuzzy correlation.-
dc.format.extent 254338 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) Econometrics of Risk, Springer Verlag, pp.273-285-
dc.title (題名) Correlation Evaluation with Fuzzy Data and its Application in the Management Science-
dc.type (資料類型) book/chapteren
dc.identifier.doi (DOI) 10.1007/978-3-319-13449-9_19-
dc.doi.uri (DOI) http://dx.doi.org/10.1007/978-3-319-13449-9_19-