International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
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Volume 11 - Issue 4 |
Published: Sep 2016 |
Authors: Aditya Kumar Anand |
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Aditya Kumar Anand . Approach to Calculate the Degree of Similarity between Generalized Trapezoidal Fuzzy Numbers. International Journal of Applied Information Systems. 11, 4 (Sep 2016), 31-36. DOI=10.5120/ijais2016451598
@article{ 10.5120/ijais2016451598, author = { Aditya Kumar Anand }, title = { Approach to Calculate the Degree of Similarity between Generalized Trapezoidal Fuzzy Numbers }, journal = { International Journal of Applied Information Systems }, year = { 2016 }, volume = { 11 }, number = { 4 }, pages = { 31-36 }, doi = { 10.5120/ijais2016451598 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2016 %A Aditya Kumar Anand %T Approach to Calculate the Degree of Similarity between Generalized Trapezoidal Fuzzy Numbers%T %J International Journal of Applied Information Systems %V 11 %N 4 %P 31-36 %R 10.5120/ijais2016451598 %I Foundation of Computer Science (FCS), NY, USA
This paper presents a new statistical approach to measure the degree of similarity between the generalized trapezoidal fuzzy numbers. Since the evolution of Fuzzy sets and logic, many researchers, mathematicians are working on the Fuzzy systems to find unhidden concepts related to it. It has been used in almost every sphere, whether it is a scientific research analysis or the pattern recognition, decision-making or the image processing. These fields and many more, widely use the similarity measure of fuzzy numbers. In this work, a simple method has been proposed to calculate the degree of similarity between the fuzzy numbers. It is one of the simplest method to find the degree of similarity between the fuzzy numbers. Complexity is reduced by utilizing the least number of parameters to calculate the degree of similarity. A comparative study between the proposed model and the existing similarity model shows that the proposed method is more accurate than the existing models, which are used to find the degree of similarity between the fuzzy numbers.