
doi: 10.1007/bf01026625
Hybrid modeling entails the combination of a numerical weather prediction model and a “symbolic” model. The latter uses symbolic objects, their characterizing attributes and sets of behavioral constrains which prescribe changes in the states of these objects as functions of time, space, and other imposed quantitative or heuristic conditions. Integration of these two modeling components for an on-line, real-time, operational system is feasible only if both the numerical and the symbolic model can be executed in a “distributed” mode, i.e. at a user's location rather than in a central weather service office. This condition entails the design of a numerical model that can run on relatively inexpensive desktop workstations or high-end PCs. Given such a capability, the output from the numerical model can be used to satisfy a number of behavioral constraints of objects (such as “thunderstorm”, “blizzard”, etc.), defined in the symbolic model. These constraints can be embedded “invisibly” as functions of time and pixel location on the computer screen, to be called upon as soon as the respective object is activated, e.g. by placing an “icon” on the screen.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
