Abstract
Cross-entropy for uncertain variables is used to measure the divergence between two uncertainty distributions. Logarithm cross-entropy and quadratic cross-entropy for uncertain variables fail to measure the degree of divergence associated with some uncertain variables; thus, this paper proposes a new definition of cross-entropy for uncertain variables as a supplement and discusses its properties. A formula of cross-entropy is derived via inverse uncertainty distributions. Moreover, this paper also defines the generalized cross-entropy of uncertain variables and investigates its properties.
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This work was supported by the Fundamental Research Funds for the Central Universities No. 2016MS65 and National Natural Science Foundation of China Grant No. 71671064.
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Gao, X., Jia, L. & Kar, S. A new definition of cross-entropy for uncertain variables. Soft Comput 22, 5617–5623 (2018). https://doi.org/10.1007/s00500-017-2534-6
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DOI: https://doi.org/10.1007/s00500-017-2534-6