Uncertainty Management in Rule Based Systems Application to Maneuvers Recognition

On Uncertain Probabilistic Data Modeling

“…Researchers proposed many approaches to modeling data uncertainties including rule-based models [1], fuzzy models [2], Dempster-Shafer theory of evidencebased models [3], and probability models [4]: Rule-based models apply an inference engine or semantic reasoner to infer uncertainty and imprecision based on the interaction of input and the rule base; Fuzzy models uses fuzzy technologies and tools such as fuzzy entities, attributes, relationship, aggregation, and constraints to model data uncertainty and imprecision; Dempster-Shafer theory of evidence-based models use Dempster-Shafer theory to represent data uncertainty and imprecision; and Probabilistic models represent data uncertainty by probabilistic theories, which is mostly relied on possible worlds model. As probabilistic models are widely used in many applications and in many different data format, such as structured, semi-structured, unstructured, and graph data, this paper is concentrated on probabilistic models of uncertain data.…”