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By directly modelling observed behaviour, the model captures the costs and effects due to both early re-screening and any late re-screening in different age groups.
However, the neural network does not easily provide insight into model behaviour; the model is explicit rather than implicit in form.
Although ignoring many aspects of seal behaviour, the model can be applied as a tool to guide further data collection and analysis, study seal ecology, and evaluate the efficacy of various conservation measures.
Likewise, if the data used to fit the parameters does not cover the complete space of system behaviour, the model parameters will not be constrained by the data, which also means that the model is too complex for the data it is being used to understand.
The fact that the truncated power law was a plausible fit for the fewer number of avalanches (note that 100, 000 is of the same order of magnitude as the number of avalanches typically reported in in vitro or in vivo studies of neuronal avalanches) is indicative of the partial scale-free behaviour the model exhibits.
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Accordingly, model calibration required that both mean behaviour and variability behaviour of the model were in accordance with real data.
The model of the cab suspension is validated by comparing the behaviour of the model with the behaviour of an experimental test rig for different vibration signals.
In case of 1) and 2), the behaviour of the model is not as expected by the modeller.
The global behaviour of the model system was studied.
The behaviour of the model is explored numerically.
To this end, we investigate the numerical behaviour of the model under such an intervention.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com