Titlebook: Combining Fuzzy Imprecision with Probabilistic Uncertainty in Decision Making; Janusz Kacprzyk,Mario Fedrizzi Book 1988 Springer-Verlag Be

欢乐东方

https://doi.org/10.1007/978-3-030-74158-7Combining fuzzy imprecision with probabilistic uncertainty raises up a number of problems connected with the development of new methods and models depending on available information. The paper considers some aspects of decision making when the initial data are fuzzy as well as incomplete.

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Advanced Packages and 3D-SoC Designs,An LP (Linear Programing) problem is studied under the assumption that the right hand sides of the contraint inequalities are independently distributed normal r.v.’s (random variables) with fuzzy mean values and fuzzy standard deviations..A version of Charnes-Cooper’s method is formulated and possible extensions of the approach are suggested.

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collateral

Confidence Intervals for the Parameters of a Linguistic Random VariableIn this paper we examine various problems of statistical inference under the presence of vagueness. More specifically, we discuss the problem of confidence estimation where the available data are imprecise. We indicate some possible applications.

genesis

On Combining Uncertainty MeasuresThis paper discusses the probabilistic structure in the problem of combination of evidence. We propose to use the theory of random sets as a general framework for combining various types of uncertainty measures such as probability measures, belief functions and possibility distributions.

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Fuzzy Evaluation of CommunicatorsIn assigning fuzzy values to propositions, we need to evaluate our belief in the source of those propositions. Thus we must assign fuzzy values to sources, considered as communicators. This paper explores some of the connections between values of propositions and values of the communicators who issue them.

Palter

Basal-Ganglia

Decision Making Based on Fuzzy Stochastic and Statistical DominanceCombining fuzzy imprecision with probabilistic uncertainty raises up a number of problems connected with the development of new methods and models depending on available information. The paper considers some aspects of decision making when the initial data are fuzzy as well as incomplete.

Platelet

Oligarchy

Decision Making in a Probabilistic Fuzzy Environmentgiven. For the decision set (in addition to the sets representing goals and constraints) the concept of probabilistic set as devised by Hirota is used. The ideas presented in the work are illustrated by means of the numerical examples.