Least-squared ordered weighted averaging operator weights

International Journal of Intelligent Systems

Volumn 23, Issue 1, 2008, Pages 33-49

  Ahn, Byeong Seok ^a   Park, Haechuri ^a  

^a Chung Ang University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION MAKING; MATHEMATICAL OPERATORS; NUMERICAL METHODS; UNCERTAINTY ANALYSIS;

MAXIMUM ENTROPY OWA (MEOWA) WEIGHTS; UNCERTAIN INTERVAL LSOWA WEIGHTS;

LEAST SQUARES APPROXIMATIONS;

EID: 38149125554     PISSN: 08848173     EISSN: 1098111X     Source Type: Journal    
DOI: 10.1002/int.20257     Document Type: Article

References (24)

1. Ahn BS. Extending Malakooti 's model for ranking multicriteria alternatives with preference strength and partial information. IEEE Trans Syst Man Cybernet A 2003;33:281-287.
2. Ahn BS. Multi-attribute decision aid with extended ISMAUT. IEEE Trans Syst Man Cybernet A 2006;36:507-520.
3. Yager RR. On ordered weighted averaging aggregation operators in mulitcriteria decision making. IEEE Trans Syst Man Cybernet 1988;18:183-190.
4. Xu ZS. An overview of methods for determining OWA weights. Int J Intell Syst 2005;20:843-865.
5. Yager RR. Fuzzy aggregation of modular neural networks with ordered weighted averaging operators. Int J Approx Reason 1995; 13:359-375.
6. Yager RR. On a semantics for neural networks based on fuzzy quantifiers. Int J Intell Sys 1992;7:765-786.
7. Yager RR. A note on weighted queries in information retrieval systems J Amer Soc Inform Sciences 1987;28:23-24.
8. Yager RR. Connectives and quantifiers in fuzzy sets. Fuzzy Set Syst 1991;40:39-75.
9. Yager RR, Filev DP. Fuzzy logic controllers with flexible structures. In: Proc Second Int Conf Fuzzy Sets and Neural Networks, Tizuka; 1992. pp 317-320.
10. Herrera F, Herrera-Viedma E, Verdegay JL. A sequential selection process in group decision making with a linguistic assessment approach. Inform Science 1995;85:223-239.
11. Herrera F, Herrera-Viedma E, Verdegay JL. Model of consensus in group decision making under linguistic assessments. Fuzzy Set Syst 1996;78:73-87.
12. Torra V. OWA operators in data modeling and reidentification. IEEE Trans Fuzzy Syst 2004;12;652-660.
13. Rinner C, Raubal M. Personalized multi-criteria decision strategies in location-based decision support. J Geogr Inform Sei 2004; 10:149-156.
14. Jiang H, Eastman JR. Application of fuzzy measures in multi-criteria evaluation in GIS. Int J Geogr Inform Sei 2000;14:173-184.
15. Rinner C, Malczewki J. Web-enabled spatial decision analysis using ordered weighted averaging (OWA). J Geogr Syst 2002;4:385-403.
16. Fernandez Salido JM, Murakami S. Extending Yager's orness concept for the OWA aggregators to other mean operators. Fuzzy Set Syst 2003:139;515-542.
17. Xu ZS, Da QL. An overview of operators for aggregating information. Int J Intell Syst 2003;18:953-969.
18. Filev D, Yager RR. On the issue of obtaining OWA operator weights. Fuzzy Set Syst 1998;94:157-169.
19. O'Hagan M. Using maximum entropy-ordered weighted averaging to construct a fuzzy neuron. In: Proc. 24th Annual IEEE Asilomar Conf on Signals Systems and Computers, Pacific Grove, CA; 1990; pp 618-623.
20. Filev D, Yager RR. Analytic properties of maximum Entropy OWA operators. Inform Science 1995;85;11-27.
21. Fuller R, Majlender P. An analytic approach for obtaining maximal entropy OWA operator weights. Fuzzy Set Syst 2001:124;53-57.
22. Fuller R, Majlender P. On obtaining minimal variability OWA operator weights. Fuzzy Set Syst 2003;136:203-215.
23. Ahn BS. On the properties of OWA operator weights functions with constant level of orness. IEEE Trans Fuzzy Syst 2006; 14:511-515.
24. Ahn BS. The OWA aggregation with uncertain descriptions on weights and input arguments. IEEE Trans Fuzzy Syst, in press.