880 resultados para Benchmark Problem


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Geomagnetic activity has long been known to exhibit approximately 27 day periodicity, resulting from solar wind structures repeating each solar rotation. Thus a very simple near-Earth solar wind forecast is 27 day persistence, wherein the near-Earth solar wind conditions today are assumed to be identical to those 27 days previously. Effective use of such a persistence model as a forecast tool, however, requires the performance and uncertainty to be fully characterized. The first half of this study determines which solar wind parameters can be reliably forecast by persistence and how the forecast skill varies with the solar cycle. The second half of the study shows how persistence can provide a useful benchmark for more sophisticated forecast schemes, namely physics-based numerical models. Point-by-point assessment methods, such as correlation and mean-square error, find persistence skill comparable to numerical models during solar minimum, despite the 27 day lead time of persistence forecasts, versus 2–5 days for numerical schemes. At solar maximum, however, the dynamic nature of the corona means 27 day persistence is no longer a good approximation and skill scores suggest persistence is out-performed by numerical models for almost all solar wind parameters. But point-by-point assessment techniques are not always a reliable indicator of usefulness as a forecast tool. An event-based assessment method, which focusses key solar wind structures, finds persistence to be the most valuable forecast throughout the solar cycle. This reiterates the fact that the means of assessing the “best” forecast model must be specifically tailored to its intended use.

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In a series of papers, Killworth and Blundell have proposed to study the effects of a background mean flow and topography on Rossby wave propagation by means of a generalized eigenvalue problem formulated in terms of the vertical velocity, obtained from a linearization of the primitive equations of motion. However, it has been known for a number of years that this eigenvalue problem contains an error, which Killworth was prevented from correcting himself by his unfortunate passing and whose correction is therefore taken up in this note. Here, the author shows in the context of quasigeostrophic (QG) theory that the error can ulti- mately be traced to the fact that the eigenvalue problem for the vertical velocity is fundamentally a non- linear one (the eigenvalue appears both in the numerator and denominator), unlike that for the pressure. The reason that this nonlinear term is lacking in the Killworth and Blundell theory comes from neglecting the depth dependence of a depth-dependent term. This nonlinear term is shown on idealized examples to alter significantly the Rossby wave dispersion relation in the high-wavenumber regime but is otherwise irrelevant in the long-wave limit, in which case the eigenvalue problems for the vertical velocity and pressure are both linear. In the general dispersive case, however, one should first solve the generalized eigenvalue problem for the pressure vertical structure and, if needed, diagnose the vertical velocity vertical structure from the latter.

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The question of what explains variation in expenditures on Active Labour Market Programs (ALMPs) has attracted significant scholarship in recent years. Significant insights have been gained with respect to the role of employers, unions and dual labour markets, openness, and partisanship. However, there remain significant disagreements with respects to key explanatory variables such the role of unions or the impact of partisanship. Qualitative studies have shown that there are both good conceptual reasons as well as historical evidence that different ALMPs are driven by different dynamics. There is little reason to believe that vastly different programs such as training and employment subsidies are driven by similar structural, interest group or indeed partisan dynamics. The question is therefore whether different ALMPs have the same correlation with different key explanatory variables identified in the literature? Using regression analysis, this paper shows that the explanatory variables identified by the literature have different relation to distinct ALMPs. This refinement adds significant analytical value and shows that disagreements are at least partly due to a dependent variable problem of ‘over-aggregation’.

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Medium range flood forecasting activities, driven by various meteorological forecasts ranging from high resolution deterministic forecasts to low spatial resolution ensemble prediction systems, share a major challenge in the appropriateness and design of performance measures. In this paper possible limitations of some traditional hydrological and meteorological prediction quality and verification measures are identified. Some simple modifications are applied in order to circumvent the problem of the autocorrelation dominating river discharge time-series and in order to create a benchmark model enabling the decision makers to evaluate the forecast quality and the model quality. Although the performance period is quite short the advantage of a simple cost-loss function as a measure of forecast quality can be demonstrated.

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Using a linear factor model, we study the behaviour of French, Germany, Italian and British sovereign yield curves in the run up to EMU. This allows us to determine which of these yield curves might best approximate a benchmark yield curve post EMU. We find that the best approximation for the risk free yield is the UK three month T-bill yield, followed by the German three month T-bill yield. As no one sovereign yield curve dominates all others, we find that a composite yield curve, consisting of French, Italian and UK bonds at different maturity points along the yield curve should be the benchmark post EMU.

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The response of the Southern Ocean to a repeating seasonal cycle of ozone loss is studied in two coupled climate models and found to comprise both fast and slow processes. The fast response is similar to the inter-annual signature of the Southern Annular Mode (SAM) on Sea Surface Temperature (SST), on to which the ozone-hole forcing projects in the summer. It comprises enhanced northward Ekman drift inducing negative summertime SST anomalies around Antarctica, earlier sea ice freeze-up the following winter, and northward expansion of the sea ice edge year-round. The enhanced northward Ekman drift, however, results in upwelling of warm waters from below the mixed layer in the region of seasonal sea ice. With sustained bursts of westerly winds induced by ozone-hole depletion, this warming from below eventually dominates over the cooling from anomalous Ekman drift. The resulting slow-timescale response (years to decades) leads to warming of SSTs around Antarctica and ultimately a reduction in sea-ice cover year-round. This two-timescale behavior - rapid cooling followed by slow but persistent warming - is found in the two coupled models analysed, one with an idealized geometry, the other a complex global climate model with realistic geometry. Processes that control the timescale of the transition from cooling to warming, and their uncertainties are described. Finally we discuss the implications of our results for rationalizing previous studies of the effect of the ozone-hole on SST and sea-ice extent. %Interannual variability in the Southern Annular Mode (SAM) and sea ice covary such that an increase and southward shift in the surface westerlies (a positive phase of the SAM) coincides with a cooling of Sea Surface Temperature (SST) around 70-50$^\circ$S and an expansion of the sea ice cover, as seen in observations and models alike. Yet, in modeling studies, the Southern Ocean warms and sea ice extent decreases in response to sustained, multi-decadal positive SAM-like wind anomalies driven by 20th century ozone depletion. Why does the Southern Ocean appear to have disparate responses to SAM-like variability on interannual and multidecadal timescales? Here it is demonstrated that the response of the Southern Ocean to ozone depletion has a fast and a slow response. The fast response is similar to the interannual variability signature of the SAM. It is dominated by an enhanced northward Ekman drift, which transports heat northward and causes negative SST anomalies in summertime, earlier sea ice freeze-up the following winter, and northward expansion of the sea ice edge year round. The enhanced northward Ekman drift causes a region of Ekman divergence around 70-50$^\circ$S, which results in upwelling of warmer waters from below the mixed layer. With sustained westerly wind enhancement in that latitudinal band, the warming due to the anomalous upwelling of warm waters eventually dominates over the cooling from the anomalous Ekman drift. Hence, the slow response ultimately results in a positive SST anomaly and a reduction in the sea ice cover year round. We demonstrate this behavior in two models: one with an idealized geometry and another, more detailed, global climate model. However, the models disagree on the timescale of transition from the fast (cooling) to the slow (warming) response. Processes that controls this transition and their uncertainties are discussed.

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We consider a generic basic semi-algebraic subset S of the space of generalized functions, that is a set given by (not necessarily countably many) polynomial constraints. We derive necessary and sufficient conditions for an infinite sequence of generalized functions to be realizable on S, namely to be the moment sequence of a finite measure concentrated on S. Our approach combines the classical results about the moment problem on nuclear spaces with the techniques recently developed to treat the moment problem on basic semi-algebraic sets of Rd. In this way, we determine realizability conditions that can be more easily verified than the well-known Haviland type conditions. Our result completely characterizes the support of the realizing measure in terms of its moments. As concrete examples of semi-algebraic sets of generalized functions, we consider the set of all Radon measures and the set of all the measures having bounded Radon–Nikodym density w.r.t. the Lebesgue measure.

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We extend extreme learning machine (ELM) classifiers to complex Reproducing Kernel Hilbert Spaces (RKHS) where the input/output variables as well as the optimization variables are complex-valued. A new family of classifiers, called complex-valued ELM (CELM) suitable for complex-valued multiple-input–multiple-output processing is introduced. In the proposed method, the associated Lagrangian is computed using induced RKHS kernels, adopting a Wirtinger calculus approach formulated as a constrained optimization problem similarly to the conventional ELM classifier formulation. When training the CELM, the Karush–Khun–Tuker (KKT) theorem is used to solve the dual optimization problem that consists of satisfying simultaneously smallest training error as well as smallest norm of output weights criteria. The proposed formulation also addresses aspects of quaternary classification within a Clifford algebra context. For 2D complex-valued inputs, user-defined complex-coupled hyper-planes divide the classifier input space into four partitions. For 3D complex-valued inputs, the formulation generates three pairs of complex-coupled hyper-planes through orthogonal projections. The six hyper-planes then divide the 3D space into eight partitions. It is shown that the CELM problem formulation is equivalent to solving six real-valued ELM tasks, which are induced by projecting the chosen complex kernel across the different user-defined coordinate planes. A classification example of powdered samples on the basis of their terahertz spectral signatures is used to demonstrate the advantages of the CELM classifiers compared to their SVM counterparts. The proposed classifiers retain the advantages of their ELM counterparts, in that they can perform multiclass classification with lower computational complexity than SVM classifiers. Furthermore, because of their ability to perform classification tasks fast, the proposed formulations are of interest to real-time applications.

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The vast majority of putative solutions to the liar paradox face the infamous revenge problem. In recent work, however, Kevin Scharp has extensively developed an exciting and highly novel ‘inconsistency approach’ to the paradox that, he claims, does not face revenge. If Scharp is right, then this represents a significant step forward in our attempts to solve the liar paradox. However, in this paper, I raise a revenge problem that faces Scharp’s inconsistency approach.

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Let X be a locally compact Polish space. A random measure on X is a probability measure on the space of all (nonnegative) Radon measures on X. Denote by K(X) the cone of all Radon measures η on X which are of the form η =

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There is something peculiar about aesthetic testimony. It seems more difficult to gain knowledge of aesthetic properties based solely upon testimony than it is in the case of other types of property. In this paper, I argue that we can provide an adequate explanation at the level of the semantics of aesthetic language, without defending any substantive thesis in epistemology or about aesthetic value/judgement. If aesthetic predicates are given a non-invariantist semantics, we can explain the supposed peculiar difficulty with aesthetic testimony.