We observe division of labour in the spatially explicit model only under given circumstances (see Additional file 1 for further details), which suggests that this outcome is unstable in these cases with small group size.
The finite element analysis shows how both modified and unmodified container models respond under given loading scenarios.
It is also useful for evaluating fundamental modeling aspects, e.g., to evaluate how model diagnostics perform under given designs.
Recovery of a theory T is needed if it does not have a model under the given semantics Sem, i.e., if the theory is Sem-inconsistent.
Furthermore, we show how to find an optimal sequence of simplification rules, such that their application yields a minimal model under a given error budget for performance estimation.
In contrast, the previously known method performs a fitting between the measurement and the spectrum model under a given set of free parameters (the shift velocity and the sweeping velocity) (Narita et al. 2013).
In most cases it happens that a model, which seems to be perfect under given settings, is outperformed by another model, when the conditions change, and that there is no model that dominates under all circumstances.
Simulation: the toolbox offers several dynamic simulation tasks (AMIGO_SModel, AMIGO_SObs and AMIGO_SData) to solve system dynamics under given values of model unknowns and given experimental schemes.
When the revised tool was compared to the analytical (STANMOD) and numerical (HYDRUS-1D) models as a susceptibility measure, it ranked particular VOCs well (e.g., benzene, carbofuran, and toluene) that were consistent with other two models under the given conditions.
In this paper, the reasons for this are displayed, and a characterization of the limit LTI model is given under quite general conditions.
