On account of the existence of uncertainty, DEA occasionally faces the situation of imprecise data, especially when a set of DMUs include missing data, ordinal data, interval data, stochastic data, or fuzzy data. Therefore, how to evaluate the efficiency of a set of DMUs in interval environments is a problem worth studying. In this paper, we discussed the new method for evaluation and ranking i...

In this paper mathematical methods for prediction of uncertain structural responses with the aid of fuzzy time series are presented. Uncertain measurments of structural loads and responses respectively at equally spaced discrete time points are modeled as fuzzy variables. Hence uncertain measurments over time are considered as time series with fuzzy data. The fuzzy variables are processed on th...

Task assignment processes and its control implying reasoning about objects and resources and their changing states are dominated by discrete or stochastic-event dynamics or both. Estimating the components position of the mobile robot provided by sensor generates unknown, hidden variables which will be model by the means of probabilistic inference taking into account incomplete and uncertain inf...

Susskind has recently shown that a relativistic string approaching the event horizon of a black hole spreads in both the transverse and longitudinal directions in the reference frame of an outside observer. The transverse spreading can be described as a branching diffusion of wee string bits. This stochastic process provides a mechanism for thermalizing the quantum state of the string as it spr...

Based on a generalized cumulative damage approach with a stochastic process describing degradation, new accelerated life test models are presented in which both observed failures and degradation measures can be considered for parametric inference of system lifetime. Incorporating an accelerated test variable, we provide several new accelerated degradation models for failure based on the geometr...

Analysis of time series from stochastic processes governed by a Langevin equation is discussed. Several applications for the analysis are proposed based on estimates of drift and diffusion coefficients of the Fokker-Planck equation. The coefficients are estimated directly from a time series. The applications are illustrated by examples employing various synthetic time series and experimental ti...

Multistage stochastic programming is a key technology for making decisions over time in an uncertain environment. One of the promising areas in which this technology is implementable, is medium term planning of electricity production and trading where decision makers are typically faced with uncertain parameters (such as future demands and market prices) that can be described by stochastic proc...

Chaotic systems share with stochastic processes several properties that make them almost undistinguishable. In this communication we introduce a representation space, to be called the complexity-entropy causality plane. Its horizontal and vertical axis are suitable functionals of the pertinent probability distribution, namely, the entropy of the system and an appropriate statistical complexity ...

Many complex systems have been shown to share universal properties of organization, such as scale independence, modularity, and self-similarity. We borrow tools from statistical physics in order to study structural preferential attachment (SPA), a recently proposed growth principle for the emergence of the aforementioned properties. We study the corresponding stochastic process in terms of its ...