this paper explains a model for analyzing and measuring the propagation of order amplifications (i.e. bullwhip effect) for a single-product supply network topology considering exogenous uncertainty and linear and time-invariant inventory management policies for network entities. the stream of orders placed by each entity of the network is characterized assuming customer demand is ergodic. in fa...

In the following paper we present an easily applicable new method for analytical representation of the maximum relative inaccuracy (error) of an indirectly measurable variable f = f(x1, x2, ..., xn) as a function of the maximum relative inaccuracies (errors) of the directly measurable variables x1, x2, ..., xn. Our new approach is more adequate for the objective reality. The gist of it is that ...

Before proceeding to the formulation of the problem we are treating in this paper, we shall remind some simple facts upon which the concepts given in the sequel are based. Let us imagine such a situation when a receiver is expecting one of the messages z belonging to a finite set Z of messages which are possible to come under the given situation. The uncertainty of the situation described is ev...

This report investigates a technique to calculate the distributions of discretization errors for a model of advection-diffusion-reaction with stochastic noise in problem data. The focus is on operator-split discretization methods. The error is decomposed into components due to the splitting and due to the discretization within each component. We present a method to estimate the distributions of...

Underspread and overspread operators are Hilbert–Schmidt operators with strictly bandlimited Kohn–Nirenberg symbols. In this paper, we prove a classical conjecture concerning the necessity of the underspread condition for the identifiability of such operator classes, and, in doing so, we exhibit a new uncertainty principle phenomenon in the time-frequency analysis of operators.

the traditional event tree analysis uses a single probability to represent each top event. however, it is unrealistic to evaluate the occurrence of each event by using a crisp value without considering the inherent uncertainty and imprecision a state has. the fuzzy set theory is universally applied to deal with this kind of phenomena. the main purpose of this study is to construct an easy metho...

Uncertainty appears to vary strongly over time, temporarily rising by up to 200% around major shocks like the Cuban Missile crisis, the assassination of JFK and 9/11. This paper o¤ers the …rst structural framework to analyze uncertainty shocks. I build a model with a time varying second moment, which is numerically solved and estimated using …rm level data. The parameterized model is then used ...

State of the art benchmarks for Twitter Sentiment Analysis do not consider the fact that for more than half of the tweets from the public stream a distinct sentiment cannot be chosen. This paper provides a new perspective on Twitter Sentiment Analysis by highlighting the necessity of explicitly incorporating uncertainty. Moreover, a dataset of high quality to evaluate solutions for this new pro...

Uncertain variable is defined as a measurable function from an uncertainty space to the set of real numbers for describing subjective uncertain phenomena, which is employed to characterize the element, component and system lifetimes in this paper. Within the framework of uncertainty theory, reliability measure and percentile lifetime are defined to measure the system reliability in this paper. ...

We propose a novel combined global/local model for active semi-supervised spectral clustering based on the principle of uncertainty reduction. We iteratively compute the derivative of the eigenvectors produced by spectral decomposition with respect to each item/image, and combine this with local label entropy provided by the current clustering results in order to estimate the uncertainty reduct...