New statistical approaches for fuzzy data

International Journal of Uncertainty, Fuzziness and Knowldege-Based Systems

Volumn 15, Issue SUPPL. 2, 2007, Pages 89-106

  Sun, Ching Min ^a   Wu, Berlin ^b  

^a Jen Wen Institute of Technology   (Taiwan)

^b NATIONAL CHENGCHI UNIVERSITY   (Taiwan)

Author keywords

Fuzzy Kruskal Wallis test; Fuzzy mean; Fuzzy median; Fuzzy mode; Fuzzy sampling survey; Human feeling

Indexed keywords

COMPUTATIONAL METHODS; MEASUREMENT ERRORS; RANDOM PROCESSES; STATISTICAL METHODS; UNCERTAINTY ANALYSIS;

FUZZY KRUSKAL WALLIS TESTS; FUZZY MEAN; FUZZY MEDIAN; FUZZY MODES; FUZZY SAMPLING SURVEY;

FUZZY SETS;

EID: 34249024230     PISSN: 02184885     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0218488507004637     Document Type: Conference Paper

References (18)

1. Calvo, T. and Mesiar, R (2001), Generalized Median. Fuzzy Sets and Systems 124, 59-61.
2. Cengiz Kahraman, Cafer Erhan Bozdag, Da Ruan and Ahmet Fahri Özok (2004), Fuzzy Sets Approaches to Statistical Parametric and Nonparametric Tests, International Journal of intelligent systems, Vol. 19, 1069-1087.
3. Filzmoser, P. and Metrika, Viertl (2004), Testing hypotheses with fuzzy data: The fuzzy p-value, Metrika, 59: 21-29
4. Friedman, M., Henne, M. and Kandel,A. (1997), Most typical values for fuzzy sets, Fuzzy Sets Systems 87, 27-37.
5. Liang, G S., & Wang, M. J. (1991), A fuzzy multicriteria decision making method for facility site selection, International Journal of Production Research 29(11), 2313-2330.
6. Liu, B. (2004), Uncertainty Theory: An Introduction to its Axiomatic Foundations, Springer, Springer, Heidelberg.
7. Lowen, R. (1990), A fuzzy language interpolation theorem, Fuzzy Sets and Systems 34, 33-38.
8. Nguyen, H. and Wu, B. (2006), Fundamentals of Statistics with Fuzzy Data, Springer-Verlag: Heidelberg.
9. Ruspini, E. (1991), Approximate Reasoning: past, present, future, Information Sciences 57, 297-317.
10. Schneider, M. and Craig, M. (1992), On the use of fuzzy sets in histogram equalization, Fuzzy Sets Systems 45, 271-278, 61.
11. Wu, B. (1995), Fuzzy statistical analysis: a new research method on the sampling survey, Research Letters of National Chengchi University 2, 65-80.
12. Wu, B. and Sun, C. (2001), Interval-valued statistics, fuzzy logic, and their use in computational semantics, Journal of Intelligent and Fuzzy Systems 11, 1-7.
13. Wu, B. and Tseng, N. (2002), A New Approach to Fuzzy Regression Models with Application to Business Cycle Analysis, Fuzzy Sets and System 130, 33-42.
14. Wu, B. and Yuang, W. (1998), Fuzzy statistics and its applications in the social science research, (with Yuang, W.) in Developing and Applications of Quantity Methods in Social Sciences, ed. Yuang, W. Institute of Social Science, Academic Sinica, 289-316.
15. Xu, R. N. and Zhai, X. Y. (1992), Extensions of the analytic hierarchical process in fuzzy environment, Fuzzy Sets and Systems 52, 251-257.
16. Yen, C. L. (1996), Using fuzzy sets in developing mathematical learning progress indicator. The Proceedings of National Science Council (part D) 6, 57-64.
17. Zadeh, L. A. (1965), Fuzzy Sets, Information and Control 8, 338-353.
18. Zimmermann, H. J. (1991), Fuzzy Set Theory and Its Applications, Boston: Kluwer Academic.