12.4 Summary and Conclusions
We solved the maximum entropy principle with imprecise side-conditions, which were modeled as fuzzy sets, producing fuzzy probability distributions. It seems very natural if you start with a fuzzy mean, variance, etc, you need to end up with a fuzzy probability distribution. Fuzzy probability distributions produce fuzzy means, variances, etc. In the next two chapters we restrict the solutions to be crisp (not fuzzy).
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12.5 References
J.J. Buckley: Entropy Principles in Decision Making Under Risk, Risk Analysis, 5(1985)303–313.
J.J. Buckley: Maximum Entropy Principle with Imprecise Side-Conditions, Soft Computing, 9(2005)507–511.
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© 2006 Springer-Verlag Berlin Heidelberg
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(2006). Fuzzy Max Entropy Principle. In: Fuzzy Probability and Statistics. Studies in Fuzziness and Soft Computing, vol 196. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33190-5_12
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DOI: https://doi.org/10.1007/3-540-33190-5_12
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