Abstract
This article presents a new approach to making decisions when information, possibly incomplete, is provided by many sources. The proposed method is based on IVFS scalar cardinality (sigma f-count). First a general algorithm is introduced, and next an application in supporting medical decisions in ovarian tumor differentiation (based on multiple diagnostic models) is presented and discussed.
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Dyczkowski, K., Stachowiak, A., Wygralak, M. (2018). A Decision-Making Model in an IVFS Environment Based on Sigma f-Count Cardinality. In: Atanassov, K., et al. Uncertainty and Imprecision in Decision Making and Decision Support: Cross-Fertilization, New Models and Applications. IWIFSGN 2016. Advances in Intelligent Systems and Computing, vol 559. Springer, Cham. https://doi.org/10.1007/978-3-319-65545-1_11
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DOI: https://doi.org/10.1007/978-3-319-65545-1_11
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