Abstract
Current researches in the domain of Information and Communication Technologies describe and extend the existing formalisms to develop systems that compute uncertain data. Indeed, handling uncertain data is a great challenge for complex systems. In this article, we provide a formal model to compute such data rigorously. Such quantities may be interpreted as either possible or probable values, added to their interdependencies. For this, the algebraic structure we defined is a vector space. We then provide a particular way for mixing such continuous quantities.
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Dubois D, Prade H (1988) Théorie des possibilités, Application à la représentation des connaissances en informatique. Masson, Paris (in French)
Zadeh LA (1978) Fuzzy sets as a basis for a theory of possibility. Fuzzy Set Syst 1:3–28
Zadeh LA (1965) Fuzzy sets. In: Information and control, vol 8. Academic Press, New York
Dantan J, Pollet Y, Taïbi S (2015) Combination of imperfect data in fuzzy and probabilistic extension classes. J Environ Account Manag 123–150. doi:10.5890/JEAM.2015.06.004
Destercke S, Dubois D, (2009) The role of generalised p-boxes in imprecise probability models. In: Proceedings of 6th international symposium on imprecise probability. Presented at ISIPTA '09, GBR, Durham, pp 179–188
Dubois D, Foulloy L, Mauris G, Prade H (2004) Probability-possibility transformations, triangular fuzzy sets, and probabilistic inequalities. Reliab Comput 10(4):273–297
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Dantan, J., Pollet, Y., Taibi, S. (2017). A Formal Model to Compute Uncertain Continuous Data. In: Bourgine, P., Collet, P., Parrend, P. (eds) First Complex Systems Digital Campus World E-Conference 2015. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-319-45901-1_8
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DOI: https://doi.org/10.1007/978-3-319-45901-1_8
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