Numerical Taxonomy Analysis with Trapezoidal Fuzzy Data
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Authors
Ali Mohammadi
- Isalamic Azad University‐Bojnourd Branch
Javad Shohani
- Mathematics PHD student, Faculty of Mathematics, University of Sistan & Baluchestan
Rajabali Borzooei
- Pure Mathematics and Faculty Member of Shahid Behshti University
Abstract
Numerical taxonomy analysis is one of the best method of grading, classifying and
comparing countries or different regions according to their development levels and
modernity, that it can be used for different grading too. In this paper, the numerical
taxonomy method with triangular fuzzy data that has been introduced by Mr.
mohammadi and his colleagues in 2010, is expended to the method of numerical
taxonomy with trapezoidal fuzzy data. So, if alternatives values, are place in diverse
indicators of triangular fuzzy values, the output of expanded method of this paper will
be the same as the numerical taxonomy method with triangular fuzzy data that has
been introduced by Mr. mohammadi and his colleagues.
Share and Cite
ISRP Style
Ali Mohammadi, Javad Shohani, Rajabali Borzooei, Numerical Taxonomy Analysis with Trapezoidal Fuzzy Data, Journal of Mathematics and Computer Science, 2 (2011), no. 1, 100--110
AMA Style
Mohammadi Ali, Shohani Javad, Borzooei Rajabali, Numerical Taxonomy Analysis with Trapezoidal Fuzzy Data. J Math Comput SCI-JM. (2011); 2(1):100--110
Chicago/Turabian Style
Mohammadi, Ali, Shohani, Javad, Borzooei, Rajabali. "Numerical Taxonomy Analysis with Trapezoidal Fuzzy Data." Journal of Mathematics and Computer Science, 2, no. 1 (2011): 100--110
Keywords
- numerical taxonomy
- trapezoidal fuzzy number
- development level.
MSC
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