118,680 research outputs found

    Uncertainty representation of grey numbers and grey sets

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    In the literature there is a presumption that a grey set and an interval-valued fuzzy set are equivalent. This presumption ignores the existence of discrete components in a grey number. In this paper new measurements of uncertainties of grey numbers and grey sets, consisting of both absolute and relative uncertainties, are defined to give a comprehensive representation of uncertainties in a grey number and a grey set. Some simple examples are provided to illustrate that the proposed uncertainty measurement can give an effective representation of both absolute and relative uncertainties in a grey number and a grey set. The relationships between grey sets and interval-valued fuzzy sets are also analysed from the point of view of the proposed uncertainty representation. The analysis demonstrates that grey sets and intervalvalued fuzzy sets provide different but overlapping models for uncertainty representation in sets

    Grey sets and greyness

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    This paper discusses the application of grey numbers for uncertainty representation. It highlights the difference between grey sets and interval-valued fuzzy sets, and investigates the degree of greyness for grey sets. It facilitates the representation of uncertainty not only for elements of a set, but also the set itself as a whole. Our results show that a grey set could be specified for interval-valued fuzzy sets or rough sets under special conditions. With the notion of grey sets and their associated degrees of greyness, various set operations between grey sets are discussed

    Hierarchical fuzzy logic based approach for object tracking

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    In this paper a novel tracking approach based on fuzzy concepts is introduced. A methodology for both single and multiple object tracking is presented. The aim of this methodology is to use these concepts as a tool to, while maintaining the needed accuracy, reduce the complexity usually involved in object tracking problems. Several dynamic fuzzy sets are constructed according to both kinematic and non-kinematic properties that distinguish the object to be tracked. Meanwhile kinematic related fuzzy sets model the object's motion pattern, the non-kinematic fuzzy sets model the object's appearance. The tracking task is performed through the fusion of these fuzzy models by means of an inference engine. This way, object detection and matching steps are performed exclusively using inference rules on fuzzy sets. In the multiple object methodology, each object is associated with a confidence degree and a hierarchical implementation is performed based on that confidence degree.info:eu-repo/semantics/publishedVersio

    Parameter estimation of a land surface scheme using multicriteria methods

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    Attempts to create models of surface-atmosphere interactions with greater physical realism have resulted in land surface schemes (LSS) with large numbers of parameters. The hope has been that these parameters can be assigned typical values by inspecting the literature. The potential for using the various observational data sets that are now available to extract plot-scale estimates for the parameters of a complex LSS via advanced parameter estimation methods developed for hydrological models is explored in this paper. Results are reported for two case studies using data sets of typical quality but very different location and climatological regime (ARM-CART and Tucson). The traditional single-criterion methods were found to be of limited value. However, a multicriteria approach was found to be effective in constraining the parameter estimates into physically plausible ranges when observations on at least one appropriate heat flux and one properly selected state variable are available. Copyright 1999 by the American Geophysical Union

    Υ and Υ′ leptonic widths, abμ, and mb from full lattice QCD

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    We determine the decay rate to leptons of the ground-state ϒ meson and its first radial excitation in lattice QCD for the first time. We use radiatively improved nonrelativistic QCD for the b quarks and include u, d, s and c quarks in the sea with u=d masses down to their physical values. We find Γðϒ → eþe−Þ ¼ 1.19ð11Þ keV and Γðϒ0 → eþe−Þ ¼ 0.69ð9Þ keV, both in good agreement with experimental results. The decay constants we obtain are included in a summary plot of meson decay constants from lattice QCD given in the Conclusions. We also test time moments of the vector current-current correlator against values determined from the b-quark contribution to σðeþe− → hadronsÞ and calculate the b-quark piece of the hadronic vacuum polarization contribution to the anomalous magnetic moment of the muon, ab μ ¼ 0.271ð37Þ × 10−10. Finally we determine the b-quark mass, obtaining in the MS scheme, ¯ m¯ bðm¯ b; nf ¼ 5Þ ¼ 4.196ð23Þ GeV, the most accurate result from lattice QCD to date

    Modelling potential movement in constrained travel environments using rough space-time prisms

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    The widespread adoption of location-aware technologies (LATs) has afforded analysts new opportunities for efficiently collecting trajectory data of moving individuals. These technologies enable measuring trajectories as a finite sample set of time-stamped locations. The uncertainty related to both finite sampling and measurement errors makes it often difficult to reconstruct and represent a trajectory followed by an individual in space-time. Time geography offers an interesting framework to deal with the potential path of an individual in between two sample locations. Although this potential path may be easily delineated for travels along networks, this will be less straightforward for more nonnetwork-constrained environments. Current models, however, have mostly concentrated on network environments on the one hand and do not account for the spatiotemporal uncertainties of input data on the other hand. This article simultaneously addresses both issues by developing a novel methodology to capture potential movement between uncertain space-time points in obstacle-constrained travel environments
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