Detection of defective sources in the setting of possibility theory

Fuzzy Sets and Systems

Volumn 158, Issue 5, 2007, Pages 555-571

  Delmotte, Francois ^a  

^a UNIVERSITÉ DE VALENCIENNES   (France)

Author keywords

Conflict; Fusion; Possibility theory; Reliability

Indexed keywords

ALGORITHMS; DATA STRUCTURES; PROBLEM SOLVING; SECURITY OF DATA;

DATA FUSION; DEFECTIVE SOURCES; POSSIBILITY THEORIES;

PROBABILITY;

EID: 33846197854     PISSN: 01650114     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.fss.2006.10.027     Document Type: Article

References (25)

1. Bloch I. Information combination operators for data fusion: a comparative review with classification. IEEE Trans. Systems Man Cybernet. A 26 1 (1996) 52-67
2. Delmotte F., and Borne P. Modelling of reliability with possibility theory. IEEE Trans. Systems Man Cybernet. 28 1 (1998) 78-88
3. Denoeux T., and Zouhal L.M. Handling possibilistic labels in pattern classification using evidential reasoning. Fuzzy Sets and Systems 122 (2001) 409-424
4. Deveughele S., and Dubuisson B. The influence of a conflict index in the frame of the adaptive combination. Proc. of CESA 1996 (1996), Lille, France 98-103
5. Dubois D., and Prade H. On several representations of uncertain body of evidence. In: Gupta M.M., and Sanchez E. (Eds). Fuzzy Information and Decision Processes (1982), North-Holland, Amsterdam 167-181
6. Dubois D., and Prade H. Representation and combination of uncertainty with belief functions and possibility measures. Comput. Intelligence 4 (1988) 244-264
7. Dubois D., and Prade H. Combination of fuzzy information in the framework of possibility theory. In: Abadi M.A., and Gonzales R.C. (Eds). Data Fusion in Robotics and Machine Intelligence (1992), Academic Press, New York 481-505
8. D. Dubois, H. Prade, Adaptive combination rules for possibility distributions, in: EUFIT 1994, Second European Congr. on Intelligent Technics and Soft Computing, 1994, pp. 48-52.
9. Dubois D., and Prade H. La fusion d'informations imprécises. Traitement du Signal 11-6 (1994) 447-458 (in French)
10. Dubois D., Prade H., and Smets P. Representing partial ignorance. IEEE Trans. Systems Man Cybernet. 26 3 (1996) 361-375
11. Elouedi Z., Mellouli K., and Smets Ph. Assessing sensor reliability for multisensor data fusion within the transferable belief model. IEEE Trans. Systems Man Cybernet. B 34 1 (2004) 782-787
12. Grabish M., Nguyen H.T., and Walker E.A. Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference (1995), Kluwer Academic Publishers, Dordrecht
13. Oussalah M. On the use of Hamacher's t-norms family for information aggregation. Inform. Sci. 153 (2003) 107-154
14. Oussalah M., Maaref H., and Barret C. New fusion methodology approach and application to mobile robotics: investigation in the framework of possibility theory. Inform. Fusion 2 (2001) 31-48
15. Oussalah M., Maaref H., and Barret C. From adaptive to progressive combination of possibility distributions. Fuzzy Sets and Systems 139 (2003) 559-582
16. Petit-Renaud S., and Denoeux T. Non parametric regression analysis of uncertain and imprecise data using belief functions. Internat. J. Approx. Reason. 35 (2004) 1-28
17. Rakar A., and Juricic D. Diagnostic reasoning under conflicting data: the application of the transferable belief model. J. Process Control 12 (2002) 55-67
18. Rossant F., and Bloch I. A fuzzy model for optical recognition of musical scores. Fuzzy Sets and Systems 141 (2004) 165-201
19. J. Schubert, Clustering belief functions based on attracting and conflicting metalevel evidence, IPMU 2002, Annecy, France, 1-5 July 2002, pp. 571-578.
20. Shooman M.L. Probabilistic Reliability: An Engineering Approach (1988), McGraw-Hill, New York
21. R.R. Yager, New modes of OWA information fusion, Internat. J. Intell. Systems (13) (1998) 661-681.
22. Yager R.R. Induced aggregation operators. Fuzzy Sets and Systems 137 (2003) 59-69
23. Yager R.R., and Kelman A. Fusion of fuzzy information with considerations for compatibility, partial aggregation and reinforcement. Internat. J. Approx. Reason. 15 (1996) 93-122
24. G. Zunino, A.M. Jolly-Desodt, D. Jolly, Indication of conflict in data fusion, in: Proc. Sicica'97, Third IFAC Symp. on Intelligent Components and Instruments for Control Applications, Annecy, France, 1997, pp. 393-398.
25. Zwick R., Carlstein E., and Budescu D.V. Measures of similarity among fuzzy concepts: a comparative analysis. Internat. J. Approx. Reason. 1 (1987) 221-242