Abstract
Nuclear safeguards evaluation aims to verify that countries are not misusing nuclear programs for nuclear weapons purposes. Experts of the International Atomic Energy Agency (IAEA) evaluate many indicators by using diverse sources, which are vague and imprecise. The use of linguistic information has provided a better way to manage such uncertainties. However, missing values in the evaluation are often happened because there exist many indicators and the experts have not sufficient knowledge or expertise about them. Those missing values might bias the evaluation result. In this contribution, we provide an imputation process based on collaborative filtering dealing with the linguistic 2-tuple computation model and a trust measure to cope with such problems.
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Rodríguez, R.M., Ruan, D., Liu, J., Calzada, A., Martínez, L. (2010). Imputing Missing Values in Nuclear Safeguards Evaluation by a 2-Tuple Computational Model. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2010. Lecture Notes in Computer Science(), vol 6113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13208-7_26
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DOI: https://doi.org/10.1007/978-3-642-13208-7_26
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