The BETEF_CF code yields long- and short-term eruption forecasting in the form of a probability distributions of expected frequencies of each node's event ("unrest per month" for node 1, "magmatic unrest" given unrest for node 2, "eruption" given magmatic unrest for node 3), see Figure 1A.
What follows is a discussion of the importance placed on non-partisanship, transparency and forecasting in the form of IFCs and how such forms and functions reflect and realise particular understanding of the problem of public debt and conceptions of the future and policy making.
Every good sailor also reviews yesterday's forecast in the form of appraisals and applies this information into a routing program.
Its Tropical Analysis and Forecast Branch (TAFB) routinely issues marine forecasts, in the form of graphics and high seas forecasts, for this area year round, with the Ocean Prediction Center having backup responsibility for this unit.
As recently as 20 years ago, forecasting came in the form of hefty books issued twice a year that detailed trendy colors, prints and silhouettes.
Good grief, even the weather forecast comes in the form of a range of numbers.
These predictions have come to fruition exactly as forecasted in the forms of software-defined networking (SDN), standardized APIs, network virtualization, and cloud computing.
It provides formal means for combining hard data and subjective information and allows forecasting the abnormal actions in the form of mathematical models, which quantify epistemic (state-of-knowledge) uncertainties in characteristics of the actions.
After three lousy snow seasons around Lake Tahoe, skiers are hopeful that El Niño's forecast precipitation will come in the form of powdery flakes, resulting in epic ski seasons like 1996 or 2011.
Called Nebula 12 it gathers meterological data from the UK-based Met Office and recreates the forecast in your home in the form of a light or indoor clouds—"wake up to a flooding yellow light on a sunny day, or below a real cloud on that overcast winter morning," they say.
These applications are namely: identification of sensitive, 'critical' parameters; computation of approximate, re-equilibrated solutions following a change (post-optimisation); robustness analysis of model forecasts to input data errors, in the form of confidence interval estimation; and the solution of problems of the bi-level, optimal network design variety.
