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Detailed simulation of anaerobic digestion (AD) requires complex mathematical models and the optimization of numerous model parameters.
Further, being based on a parameterized network evolution model, it requires the estimation of numerous model parameters.
Most studies attempt to solve the problem by training numerous model parameters from a large dataset, but this might incur inconsistent results.
Monitoring the behavior of numerous model parameters, not just those of interest, as is the case in this study, will provide the best opportunity to confidently confirm convergence when using a Bayesian approach.
However, this depends on numerous model parameters and obligates selective information on specific growth rate of microbes, biofilm thickness and density, values of diffusivity, partition, yield and distribution coefficients, intrinsic adsorption, and so forth [ 19– 219.
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Assessment of uncertainty in land surface models is complex, mainly because of the numerous sources of error from model parameters, initial states, input forcing data, and the model structure.
However, numerous alternative methods exist to fit model parameters from measured data.
Model parameters.
Table 1 SCOPE model parameters.
Table 1: Microclimate model parameters.
Figure 9: Influence of different model parameters on model outcome.
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