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In application, a model framework of urban water metabolism was used as an example to analyze the natural hydrological processes and social water metabolism in an urban ecosystem.
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In applications a probability model is rarely known exactly and must be constructed from a combination of theoretical analysis and experimental data.
The combined module is tested in the applications in a model house.
In each application, a baseline model should be established with a recent census.
This is the case, for example, when consolidating, redesigning, and redeploying an application in a model-driven architecture.
In plant breeding, application of a model for macro- and micro-environmental sensitivities is also highly relevant since G × E interactions are generally very strong and uniformity of crops is very important.
In a typical application, a classification model is used to combine multiple biomarkers (predictors) to predict a binary outcome such as diseased/nondiseased, responders/non-responders to therapy, etc.
We did this because binary data are interpreted by MrBayes as analogous to genetic 'restriction sites.' The restriction site model in MrBayes is a direct application of a model for rate asymmetry in DNA data.
In contrast to the default values of zero, this allows the model to be simulated directly in CellDesigner and permits the application of a model optimization procedure.
Since the data maps were initialized with a minimum density of 10 g/m2 to account for movement between triangular elements that is not simulated in this model application, a difference between model output and the data value falling within 20 g/m2 was considered a "perfect" match.
However, as it often happens in applications, when modelling a realistic problem, one may decide to describe the problem in terms of differential equations or in terms of difference equations.
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