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.

Authors

Jérôme Dantan

Machine Learning Methods e-session