The 2-tuple linguistic computational model. advantages of its linguistic description, accuracy and consistency

International Journal of Uncertainty, Fuzziness and Knowldege-Based Systems

Volumn 9, Issue SUPPL., 2001, Pages 33-48

  Herrera, F ^a   Martinez, L ^b  

^a UNIVERSITY OF GRANADA   (Spain)

^b UNIVERSITY OF JAÉN   (Spain)

Author keywords

Aggregation; Computing with Words; Linguistic preference variables

Indexed keywords

EID: 0346977257     PISSN: 02184885     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0218488501000971     Document Type: Article

References (25)

1. L.A. Zadeh, The Concept of a Linguistic Variable and Its Applications to Approximate Reasoning. Part I, Information Sciences 8 (1975) 199-249, Part II, Information Sciences 8 (1975) 301-357, Part III, Information Sciences 9 (1975) 43-80.
2. L.A. Zadeh, The Concept of a Linguistic Variable and Its Applications to Approximate Reasoning. Part I, Information Sciences 8 (1975) 199-249, Part II, Information Sciences 8 (1975) 301-357, Part III, Information Sciences 9 (1975) 43-80.
3. L.A. Zadeh, The Concept of a Linguistic Variable and Its Applications to Approximate Reasoning. Part I, Information Sciences 8 (1975) 199-249, Part II, Information Sciences 8 (1975) 301-357, Part III, Information Sciences 9 (1975) 43-80.
4. G. Bordogna and G. Pasi, A Fuzzy Linguistic Approach Generalizing Boolean Information Retrieval: A Model and Its Evaluation, J. of the American Society for Information Science 44 (1993) 70-82.
5. E. Herrera-Viedma, Modeling the Retrieval Process of an Information Retrieval System Using an Ordinal Fuzzy Linguistic Approach. Journal of the American Society for Information Science , Vol 52 No 6 (2001) 460-475.
6. R.R. Yager, Protocol for Negotiations among Multiple Intelligent Agents, in: J. Kacprzyk, H. Nurmi and M. Fedrizzi Eds., Consensus Under Fuzziness. (Kluwer Academic Publishers, 1996) 165-174.
7. F.Herrera, E. López, C. Mendaña, M.A. Rodríguez, A Linguistic Decision Model for Personnel Management Solved with a Linguistic Biobjective Genetic Algorithm, Fuzzy Sets and Systems 118 (2001) pp. 47-64.
8. G.I. Adamopoulos, G.P. Pappis, A Fuzzy Linguistic Approach to a Multicriteria-sequencing Problem, European Journal of Operational Research 92 (1996) 628-636.
9. G. Bordogna, G. Pasi, A Linguistic Modeling of Consensus in Group Decision Making Based on OWA operators, IEEE Trans. on Systems, Man and Cybernetics, Part A: Systems and Humans 27 (1997) 126-132.
10. F. Herrera, E. Herrera-Viedma, J.L. Verdegay, A Model of Consensus in Group Decision Making Under Linguistic Assessments, Fuzzy Sets and Systems 79 (1996) 73-87.
11. R.R. Yager, An Approach to Ordinal Decision Making, Int. J. of Approximate Reasoning, 12 (1995) 237-261.
12. F. Herrera, E. Herrera-Viedma, J.L. Verdegay, A Sequential Selection Process in Group Decision Making with a Linguistic Assessment Approach, Information Science, 85 (1995) 223-239.
13. F. Herrera and L. Martínez, A Model based on Linguistic 2-tuples for Dealing with Multigranularity Hierarchical Linguistic Contexts in Multiexpert Decision-Making. IEEE Transactions on Systems, Man and Cybernetics. Part B: Cybernetics, Vol 31, No 2 (2001) 227-234.
14. Roubens M., Fuzzy Sets and Decision Analysis, Fuzzy Sets and Systems 90 (1997) 199-206.
15. P. Chang, Y. Chen, A Fuzzy MCDM Method for Technology Transfer Strategy Selection in Biotechnology, Fuzzy Sets and Systems 63 (1994) 131-139.
16. R. Degani and G. Bortolan, The problem of Linguistic Approximation in Clinical Decision Making, Int. Journal of Approximate Reasoning 2 (1988) 143-162
17. M. Delgado, J.L. Verdegay and M.A. Vila, On Aggregation Operations of Linguistic Labels, Int. J. of Intelligent Systems 8 (1993) 351-370.
18. F. Herrera and L. Martínez, A 2-tuple Fuzzy Linguistic Representation Model for Computing with Words, IEEE Trans. on Fuzzy Systems, Vol 8, No 6 (2000) 746-752.
19. P.P. Bonissone and K.S. Decker, Selecting Uncertainty Calculi and Granularity: An Experiment in Trading-off Precision and Complexity, in: L.H. Kanal and J.F. Lemmer, Eds., Uncertainty in Artificial Intelligence (North-Holland, 1986) 217-247.
20. D. Dubois and H. Prade, Fuzzy Sets and Systems: Theory and Applications, Academic, New York, 1980.
21. Q. Zhu and E.S. Lee, Comparison and Ranking of Fuzzy Numbers. , in: J. Kacprzyk and M. Fedrizzi Eds., Fuzzy Regression Analysis. (Physica-Verlag, 1992) 21-44.
22. K. Kim, K.S. Park, Ranking Fuzzy Numbers with Maximizing Set and Minimizing Set, Fuzzy Sets and Systems 35 (1990) 143-150.
23. P. Chang, Y. Chen, Fuzzy Number in Business Conditions Monitoring Indicators: Fuzzy Set Methodologies in Economic Condition, in:Fuzzy Engineeting toward Human Friendly Systems (Proceedings of the International Fuzzy Engineering Symposium 91, Yokohama, Japan) 2 (1991) 1091-1100.
24. M.A. Brown, L.G. Berry, R.K. Goel, Guidelines for Successfully Transferring Goverment-Sponsored Innovations, Research Policy 20 (1991) 121-143.
25. F. Herrera and L. Martínez, A Fusion Method for Multi-Granularity Linguistic Information based on the 2-tuple Fuzzy Linguistic Representation Model, Dept. Computer Science and A.I., University of Granada, Technical Report#DECSAI-990107, 1999. (http://decsai.ugr.es/̃herrera/public.html)