Algorithms for translating data into model parameters should not delay model execution and decision making.
Knowledge of LiDAR measurement uncertainty and its propagation into derived geospatial products is important for conscientious application of LiDAR products to environmental modeling, planning and decision making.
Furthermore, specific simulation-based experiment is implemented to demonstrate the research methodology on correlation between urban form and energy performance, in which the workflow is summarized as follows: definition of constants and variables, modeling, simulation, data sorting and decision making.
Having said this, the proposed framework could be adapted to deal with the treatment of non-Bayesian models of learning and decision making.
Bi- and multi-stable networks have been used, for instance in models of visual perception and decision making [23 25].
Their models for economic analysis and decision making take into consideration the psychological, social, and other non-economic factors that guide decision-makers' behavior.
Unfortunately, such discussions often fall prey to the so-called "deficit model" of the relationship between science and decision making.
There have been many studies on the modeling of a relation between emotion and decision making.
The presence of noise might mask the information that the data hold, thereby compromising data interpretation, model generation and decisions making.
It is our hope that DUET-H/WQ contributes to making uncertainty estimation a routine data collection and reporting procedure and thus enhances environmental monitoring, modeling, and decision-making.
With new satellite missions being launched every year, new types of earth science data are being incorporated into science models and decision-making systems in a broad array of organizations.
