Accordingly, philosophers of science are beginning to abandon the notion that laws are central to science, focusing instead on the search for symmetries in physics, on the differing uses of approximate generalizations in biology, and on the deployment of models in numerous areas of the sciences.
It deals with specific issues in the conceptualization, development, solution and deployment of models for applications in many domains of research, business, manufacturing and production.
Three examples based on terrestrial carbon accounting at a range of spatial scales (point, landscape, continental and global) are used to illustrate major COINS features, including flexibility in the spatial deployment of models, the ability to combine different models within the same simulation, and Monte Carlo sensitivity analyses.
The deployment of models systems, such as Drosophila, that offer varied and powerful tools for genetic analysis, is an even more recent occurrence.
Furthermore, Hestenes (1992) explains that modeling in kinematics involves three practices: development of a model; exploring the ramifications of the model in order to investigate the complex interactions in the phenomena; and deployment of the model in order to iteratively match it to empirical phenomena and data.
We should not, however, think that the deployment of this model was due to the explicit decisions of some central controlling agency.
Next, we define key terminologies used in the scientific investigation & deployment of our model in the revenue optimization problem.
It seems therefore that the differences in term of satisfaction increase with progressive deployment of the model (being the greater among employees of organisations with Gold than Silver Q Awards).
More qualitative modelling approaches are also emerging that can guide the development and deployment of quantitative models, and these can be supplemented by varied data-driven modelling approaches that can achieve new explanatory insights from observational datasets.
The transparency of models in terms of data sources and model structures is recognised by most authors as a crucial issue for the future deployment of the models.
The particular focus of this paper is on the mapping between components in different tools with more than one modeling depth, the level of detail respectively, through deployment of feature modeling.
