Computational framework for the method of decision making with imprecise probabilities

The paper is devoted to the development of a computational framework for one of the progressively developing methods for decision making under uncertainty, the method using a non-expected fuzzy-number-valued utility function represented by a fuzzy integral with fuzzy-number-valued fuzzy measure. The...

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Hauptverfasser:	Musayev, A.F., Alizadeh, A.V., Guirimov, B.G., Huseynov, O.H.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Computer networks Control systems Decision making differential evolution fuzzy Choquet integral Fuzzy control fuzzy measure Fuzzy neural networks Fuzzy systems fuzzy utility function imprecise probabilities Neural networks nonexpected utilit Petroleum Probability second-order uncertainty soft computingy Testing
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Beschreibung
Zusammenfassung:	The paper is devoted to the development of a computational framework for one of the progressively developing methods for decision making under uncertainty, the method using a non-expected fuzzy-number-valued utility function represented by a fuzzy integral with fuzzy-number-valued fuzzy measure. The method and the underlying computational framework have shown its effectiveness tested on a set of examples.
DOI:	10.1109/ICSCCW.2009.5379428