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Measures of uncertainty for imprecise probabilities: An axiomatic approach.

, and . Int. J. Approx. Reason., 51 (4): 365-390 (2010)

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Imprecision indices: axiomatic, properties and applications., and . Int. J. General Systems, 44 (7-8): 812-832 (2015)Applying models of imprecise probabilities in the mathematical theory of criteria importance., and . Autom. Remote. Control., 78 (8): 1460-1473 (2017)Conditioning of Imprecise Probabilities Based on Generalized Credal Sets., and . ECSQARU, volume 11726 of Lecture Notes in Computer Science, page 374-384. Springer, (2019)Load balancing algorithms based on gradient methods and their analysis through algebraic graph theory., and . J. Parallel Distributed Comput., 68 (2): 209-220 (2008)Metrical Approach to Measuring Uncertainty., and . IPMU (2), volume 1238 of Communications in Computer and Information Science, page 124-136. Springer, (2020)The Recognition of Roadbed Based on Fuzzy Etalons., , and . IFSA-EUSFLAT, Atlantis Press, (2015)Modelling uncertainty with generalized credal sets: application to conjunction and decision., and . Int. J. Gen. Syst., 47 (1): 67-96 (2018)Various Representations and Algebraic Structure of Linear Imprecision Indices., and . EUSFLAT Conf. (1), page 297-304. Universitas Ostraviensis, (2007)Measuring Uncertainty for Interval Belief Structures and its Application for Analyzing Weather Forecasts., and . EUSFLAT/IWIFSGN (1), volume 641 of Advances in Intelligent Systems and Computing, page 273-285. Springer, (2017)The Choice of Generalized Dempster-Shafer Rules for Aggregating Belief Functions Based on Imprecision Indices., and . Belief Functions, volume 8764 of Lecture Notes in Computer Science, page 21-28. Springer, (2014)