Fuzzy harmonic mean operators
International Journal of Intelligent SystemsPublished 31 December 2008
Zeshui Xu
Citations100
SJR quartileQ1
SJR score1.14
SNIP1.40
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TL;DR
This paper investigates the situations in which the input data are expressed in fuzzy values and develops some fuzzy harmonic mean operators, which can be reduced to aggregate interval or real numbers, and presents an approach to multiple attribute group decision making.
Abstract
Harmonic mean is a conservative average, which is widely used to aggregate central tendency data. In the existing literature, the harmonic mean is generally considered as a fusion technique of numerical data information. In this paper, we investigate the situations in which the input data are expressed in fuzzy values and develop some fuzzy harmonic mean operators, such as fuzzy weighted harmonic mean operator, fuzzy ordered weighted harmonic mean operator, fuzzy hybrid harmonic mean operator, and so on. Especially, all these operators can be reduced to aggregate interval or real numbers. Then based on the developed operators, we present an approach to multiple attribute group decision making and illustrate it with a practical example. © 2008 Wiley Periodicals, Inc.
Keywords
Computer ScienceDecision SciencesMathematics
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