Imputing missing values in nuclear safeguards evaluation by a 2-tuple computational model

Rosa Rodriguez, Da Ruan, Jun Liu, Alberto Calzada, Luis Martinez

    Research outputpeer-review


    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.
    Original languageEnglish
    Title of host publicationArtificial Intelligence and Soft Computing
    Place of PublicationHeidelberg, Germany
    StatePublished - Jun 2010
    EventICAISC 2010 - 10th International Conference on Artificial Intelligence and Soft Computing - ICAISC, Zakopane
    Duration: 13 Jun 201017 Jun 2010

    Publication series

    NameLecture Notes in Artificial Intelligence (LNAI)


    ConferenceICAISC 2010 - 10th International Conference on Artificial Intelligence and Soft Computing

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