Correlation Evaluation with Fuzzy Data and its Application in the Management Science

  • Berlin WuEmail author
  • Wei-Shun Sha
  • Juei-Chao Chen
Part of the Studies in Computational Intelligence book series (SCI, volume 583)


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.


Membership Function Fuzzy Number Fuzzy Measure Fuzzy Data Fuzzy Time Series 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Mathematical SciencesNational Cheng Chi UniversityTaipeiTaiwan
  2. 2.Graduate Institute of Business AdministrationFu Jen Catholic UniversityNew TaipeiTaiwan
  3. 3.Department of Statistics and Information ScienceFu Jen Catholic UniversityNew TaipeiTaiwan

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