An overview on the 2-tuple linguistic model for computing with words in decision making: Extensions, applications and challenges
By Luis Martínez-López, Francisco Herrera. Information Sciences, 2012
509 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Theory and Mathematics, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/91428d3e324ea224e9b4eec0a9c9d9a9ec228511
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Zeshui Xu
- Enrique Herrera-Viedma
- Francisco Herrera
- Francisco Chiclana
- Luis Martínez-López
- Jian Wu
- Rosa M. Rodríguez
- Luis Martínez
In Computational Theory and Mathematics
- Zeshui Xu
- Francisco Herrera
- Enrique Herrera-Viedma
- Luis Martínez-López
- Francisco Chiclana
- Jian Wu
- Luis Martínez
- Rosa M. Rodríguez
In Management Science and Operations Research
- Zeshui Xu
- Enrique Herrera-Viedma
- Francisco Herrera
- Francisco Chiclana
- Luis Martínez-López
- Jian Wu
- Rosa M. Rodríguez
- Huchang Liao
Citations in the corpus
- Interval-valued hesitant fuzzy linguistic sets and their applications in multi-criteria decision-making problems (2014, background): “However, as was depicted by Martínez and Herrera [28], these approaches possess certain advantages, but this does not mean that they can successfully model and solve all types of problems.”
- Managing Multigranular Linguistic Distribution Assessments in Large-Scale Multiattribute Group Decision Making (2017, background): “Moreover, according to the CW scheme [7], [43], it is also crucial to obtain interpretable final linguistic results to decision makers.”
- Trust based consensus model for social network in an incomplete linguistic information context (2015, background): “The aim of this paper is to present a new trust based consensus model for social network in a 2–tuple linguistic context [20, 21, 26, 38] under incomplete information.”
- Hesitant Fuzzy Sets: State of the Art and Future Directions (2014, background): “Different linguistic models have been presented in the literature [16, 25, 26, 28, 34] to model linguistic information.”