13.4 Summary and Conclusions
In this chapter we showed how to solve the maximum entropy problem with imprecise side-conditions for a crisp (non-fuzzy) discrete probability distribution. The next step would be to solve for a crisp continuous probability density. That is the topic of the next chapter.
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13.5 References
R.E. Bellman and L.A. Zadeh: Decision-Making in a Fuzzy Environment, Management Science, 17(1970)B141–B164.
J.J. Buckley: Risk Analysis, 5(1985)303–313.
J.J. Buckley: Maximum Entropy Principle with Imprecise Side-Conditions II: Crisp Discrete Solutions, Soft Computing. To appear.
Frontline Systems (www.frontsys.com).
Maple 9, Waterloo Maple Inc., Waterloo, Canada.
www.solver.com.
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(2006). Max Entropy: Crisp Discrete Solutions. 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_13
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DOI: https://doi.org/10.1007/3-540-33190-5_13
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