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Two new methods for ranking of Z‐numbers based on sigmoid function and sign method
Author(s) -
Ezadi Somayeh,
Allahviranloo Tofigh,
Mohammadi Salar
Publication year - 2018
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.21987
Subject(s) - ranking (information retrieval) , sigmoid function , sign (mathematics) , computer science , function (biology) , fuzzy number , fuzzy logic , mathematics , data mining , artificial intelligence , algorithm , fuzzy set , artificial neural network , mathematical analysis , evolutionary biology , biology
This paper introduces two processes of ranking methods on Z‐numbers that are effectively able to deal with uncertain decision‐making data. Decision making is based on recommended Z‐ numbers. For this purpose first, the Z‐number is transformed to a fuzzy number and then the ranking method by using the sigmoid function and the sign method is used to mention fuzzy numbers. For the next step, the method is extended to related Z‐numbers. Finally, we use it to prioritize the items and solve some examples.