The problem of over-running in hard real-time systems poses critical risks to the hardware under control. The imprecise computation technique offers an effective way of resource utilization in these cases. We introduce Imprecise-DEVS (IDEVS), a model-driven approach to develop real-time and embedded applications based on the DEVS (Discrete Event Systems Specification) formalism. This approach c...

A topos of presheaves can be seen as an extension of classical set theory, where sets vary over informational states, therefore it is a powerful and expressive mathematical framework. I introduce a suitable topos of presheaves where imprecise probabilities and imprecise probabilistic reasoning can be represented. In this way we obtain a mathematical definition of imprecise-probabilistic sets. A...

Imprecise-information processing is an important component of artificial intelligence (including computational intelligence). With the development of information and intelligence sciences and technologies as well as the rise in social requirements, imprecise-information processing is becoming more and more important and urgent, and it will play an indispensable role in intelligent systems, espe...

In the portfolio selection problem, the manager considers several objectives simultaneously such as the rate of return, the liquidity and the risk of portfolios. These objectives are conflicting and incommensurable. Moreover, the objectives can be imprecise. Generally, the portfolio manager seeks the best combination of the stocks that meets his investment objectives. The imprecise Goal Program...

In this article, we investigate the measurement of performance in DMUs in which input and/or output values are given as imprecise data. By imprecise data, we mean that in some cases, we only know that the actual values are inside certain intervals, and in other cases, data are specified only as ordinal preference information. In this article, we present two distinct perspectives for determining...

We extend functional dependencies (FDs), which are the most fundamental integrity constraints that arise in practice in relational databases, to be satissed in an imprecise relation. The problem we tackle is the following: given an imprecise relation r over a relation schema R and a set of FDs F over R, what is the most precise approximation of r, which is also consistent with respect to F. We ...

recently, farzipoor saen [journal of the operational research society, 60(11), 1575–1582 (2009)] proposed a method based on data envelopment analysis to identify optimistic efficient suppliers in the presence of nondiscretionary factors-imprecise data. this short communication aims at showing a computational error in computing the value of preference intensity parameter in farzipoor saen’s [1] ...

This paper investigates the possibility of a frequentist interpretation of imprecise probabilities, by generalizing the approach of Bernoulli’s Ars Conjectandi. That is, by studying, in the case of games of chance, under which assumptions imprecise probabilities can be satisfactorily estimated from data. In fact, estimability on the basis of finite amounts of data is a necessary condition for i...

data envelopment analysis (dea) is a method for measuring the relative efficiencies of a set of decision-making units (dmus) that use multiple inputs to produce multiple outputs. in this paper, we study the measurement of dmu performances in dea in situations where input and/or output values are given as imprecise data. by imprecise data we mean situations where we only know that the actual val...