Traditional probabilistic description of uncertainty is based on additive probability measures. To describe nonprobabilistic uncertainty, it is therefore reasonable to consider non-additive measures. An important class of non-additive measures are possibility measures, for which μ(A ∪ B) = max(μ(A), μ(B)). In this paper, we show that possibility measures are, in some sense, universal approximat...

Abstract Traditional approaches for process optimization start by fitting a model and then optimizing the model to obtain optimal operating settings. These methods do not account for any uncertainty in the parameters of the model or in the form of the model. Bayesian approaches have been proposed recently to account for the uncertainty on the parameters of the model, assuming the model form is ...

This paper presents the results of a study aimed at assessing the eŒects of input uncertainty on the outcome of a raster-based model for structural landscape classiŽ cation. The model uses a DEM and a land-cover map as input, and calculates four structural indices from these data. The Ž rst two indices determine the openness of the landscape, the other two determine the degree of landscape homo...

making capital and investment is the main driving forces of economic development. based on the investment sensitivity to the changes of some of macro-economic variables and risk and uncertainty, the present study evaluated the effective factors on investment in private sector in iran during 1980-2007. at first, the uncertainty variables of real informal exchange rate, nominal interest rate and ...

The use of land cover change map is subject to error propagation from multi-temporal land cover classification maps. Understanding the factors determining error propagation to land-cover change maps helps to select appropriate classification models and characterize the associated uncertainties. In this paper, we presented a simulation analysis on the rates of error propagation for both non-cont...

The modulation spaces M m (R ) quantify the time-frequency concentration of functions and distributions. The first main result of this paper proves embeddings of certain modulation spaces into VMO, the space of functions with vanishing mean oscillation. The second main result proves that the Zak transform maps certain modulation spaces on R into modulation spaces on R. These two results allow u...

The quantification and analysis of uncertainties is important in all cases where maps and models of uncertain properties are the basis for further decisions. Once these uncertainties are identified, the logical next step is to determine how they can be reduced. Information theory provides a framework for the analysis of spatial uncertainties when different subregions are considered as random va...

X-ray temperature measurements of clusters of galaxies are now reaching to redshifts high enough to constrain Ω0. A redshift-dependent relation that maps these X-ray temperatures to the virial masses of clusters is an essential ingredient when one is trying to determine cosmological parameters from cluster evolution. Most such relations assume that clusters form from top-hat perturbations that ...

s: In this paper, we propose an algorithm that leverages road markings obtained from monocular camera images to estimate accurate vehicle position. Our method generates sub-maps containing only road markings that increase the confidence of the matching to improve the accuracy of the loop detection. The cumulative error is compensated by the detected loop, thereby increasing the overall global a...