Numerical Taxonomy Analysis with Trapezoidal Fuzzy Data


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.


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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


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