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Although the volume and variety of medical data make its analysis a big challenge, advances in medical imaging could make individualized care more practical [ 33] and provide quantitative information in variety of applications such as disease stratification, predictive modeling, and decision making systems.
The problem of less and/or even lack of information and uncertainty in modeling and decision making plays a key role in many engineering problems; so that, it results in designers and engineers could not reach to sure solutions for the problems under consideration.
The numerical methods and computing techniques have become suitable and efficient tools for formulating and testing conceptual models and mathematical theories that can integrate diverse information about geology, physics, construction technique, economy and their interactions, and their impacts on the environment on one compact modeling and decision making platform.
The proposed mechanism introduces the importance of strategic buyers for suppliers in modeling and decision making process.
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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.
Algorithms for translating data into model parameters should not delay model execution 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.
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.
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