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The model variables are common parameters (i.e. pressures and temperatures) on chilled water side in chiller systems.
We show that if model variables are fitted to known roost locations, these variables may be used as numerical descriptors of foraging patterns.
There is a more fundamental classification of models based on the way model states are generated and the way model variables are handled.
Then, model variables are reparameterized as a linear combination of important models in the initial ensemble by Singular Value Decompostion SVDD) and Simultaneous Perturbation Stochastic Algorithm is applied to solve coefficients of this combination.
From Table 1, we confirmed that selected model variables are different among the subjects.
Because of the word limits, the model variables are not introduced and statistical tables are not listed.
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Further exploration of model variables is warranted.
The model variables were estimated using values from literature.
The effects of local settings and model variables were relatively small, making the results more generally applicable.
Specifically, the limiter applied to the turbulence model variables was found to significantly influence the overall convergence behavior.
Schwartz's norm-activation model variables were collected.
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