Nuclear safeguards evaluation aims to verify that countries are misusing nuclear programs for nuclear weapons purposes. Experts from International Atomic Energy Agency (IAEA) evaluate indicators using several sources such as State declarations, on-site inspections, non-safeguards IAEA databases and other open sources. These evaluations are aggregated to obtain a global assessment, which are not precise because the available information is vague or too difficult to be understood. Moreover, experts cannot often assess all evaluations because of too many indicators or because of the lack of sufficient expertise about some of indicators. This results in many missing values in the evaluations that can change final results. In this contribution, we impute the missing values by a 2-tuple computational model that calculates a trust measure to express the reliability of the imputations.
|Name||Lecture Notes in Artificial Intelligence (LNAI)|
|Conference||ICAISC 2010 - 10th International Conference on Artificial Intelligence and Soft Computing|
|Period||2010-06-13 → 2010-06-17|