Intuitionistic Fuzzy Aggregation Operators
By Zeshui Xu. IEEE transactions on fuzzy systems, 2007
2,527 citations recorded by the source corpus.
Subfields: Ecological Modeling, Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/258919dc0c492dce59fa999ddf286ec3aaf15e36
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In Ecological Modeling
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Citations in the corpus
- GRA method for multiple attribute decision making with incomplete weight information in intuitionistic fuzzy setting (2010, methodology): “In the following, the intuitionistic fuzzy weighted averaging (IFWA) operator [46] and maximizing deviation method are used to solve the above multiple attribute decision-making problems (for short, Wei’s methods [22]).”
- Linear Diophantine fuzzy set and its applications towards multi-attribute decision-making problems (2019, positive): “The binary relation ≤ ( M , A ) on LDFN ( Q ) can be defined as (cid:7) We can easily proof this by using the LDFS operations and by mathematical induction same as used in [47] by Xu.”
- An Extended PROMETHE II Multi-Criteria Group Decision Making Technique Based on Intuitionistic Fuzzy Logic for Sustainable Energy Planning (2016, background): “(16) (Xu 2007).”
- Intuitionistic Fuzzy Information Aggregation Using Einstein Operations (2012, methodology): “However, what is it like the expression of the intuitionistic fuzzy aggregation operator based on the Einstein operations? What is the relationship between the new aggregation operators and those proposed by Xu [59], [62] in aggregation process? Therefore, the focus of this paper is to develop some ”
- An approach to multiattribute decision making with interval-valued intuitionistic fuzzy assessments and incomplete weights (2009, methodology): “Built upon the concepts of score and accuracy functions, Xu [32] devises a new approach to comparing two IFNs.”
- Hesitant fuzzy information aggregation in decision making (2011, background): “Xu and Yager [12,13] gave some intuitionistic fuzzy aggregation operators as listed below: For a collection of IFVs ai(i = 1,2, .”
- TOPSIS Method Based on Correlation Coefficient under Pythagorean Fuzzy Soft Environment and Its Application towards Green Supply Chain Management (2021, background): “Then, the PFSWA operator may be reduced to the IFWA operator [48].”
- Pythagorean Fuzzy Information Measures and Their Applications (2017, background): “(1) E1(M) = 1 |X| ∑ x∈X π2 M (x)+1−|μ(2)M (x)−ν2 M (x)| π2 M (x)+1+|μ(2)M (x)−ν2 M (x)| ; (2) E2(M) = 1 |X| ∑ x∈X 1−|μ(2)M (x)−ν2 M (x)| 1+|μ(2)M (x)−ν2 M (x)| ; (3) E3(M) = ∑ x∈X (1−|μ(2)M (x)−ν2 M (x)|) ∑ x∈X (1+|μ(2)M (x)−ν2 M (x)|) ; (4) E4(M) = 1 − 1 |X| ∑ x∈X |μ(2)M (x) − ν2 M (x)|; (5) E5(M) ”
- Induced generalized intuitionistic fuzzy operators (2011, methodology): “If we calculate the expected values Vik (k = 1,2,3) of each alternative Yiby the IFWG operator [34] or IFWA operator [31], the corresponding results are given in Tables 8 and 9.”
- Some q‐rung orthopair fuzzy Heronian mean operators in multiple attribute decision making (2018, neutral): “…is smaller than ̃𝑝 2 , denoted by ̃𝑝 1 < ̃𝑝 2 ; if 𝑆 ( ̃𝑝 1 ) = 𝑆 ( ̃𝑝 2 ) , then (1) if 𝐻 ( ̃𝑝 1 ) = 𝐻 ( ̃𝑝 2 ) , then ̃𝑝 1 and ̃𝑝 2 represent the same information, denoted by ̃𝑝 1 = ̃𝑝 2 ; (2) if 𝐻 ( ̃𝑝 1 ) < 𝐻 ( ̃𝑝 2 ) , ̃𝑝 1 is smaller than ̃𝑝 2 , denoted by ̃𝑝 1 < ̃𝑝 2 .”
- Large-scale group decision making model based on social network analysis: Trust relationship-based conflict detection and elimination (2019, methodology): “we can utilize the the intuitionistic fuzzy average operator [54] on the obtained final group decision”
- Some Results for Pythagorean Fuzzy Sets (2015, background): “(3) p 1 ⊕ p 2 = (ν1, μ1) ⊕ (ν2, μ2) = ( √ ν2 1 + ν2 2 − ν2 1ν(2) 2 , μ1μ2) (p1 ⊗ p2) = (μ1μ2, √ ν2 1 + ν2 2 − ν2 1ν(2) 2 ) = ( √ ν2 1 + ν2 2 − ν2 1ν(2) 2 , μ1μ2) = p 1 ⊕ p 2.”
- Ranking the sustainability performance of pavements: An intuitionistic fuzzy decision making method (2014, methodology): “To establish aggregated IF super decisionmatrix, IFWAAoperator [39] is utilized.”
- Choquet integrals of weighted intuitionistic fuzzy information (2010, methodology): “In this case, the IFCA operators (6) and (7) reduce to the intuitionistic fuzzy ordered weighted averaging (IFOWA) operator [19]:”