Agent-based Ecological Model Calibration - on the Edge of a New Approach
Pereira, Antonio, Duarte, Pedro, Reis, Luis Paulo
–arXiv.org Artificial Intelligence
- In every mathematical model, parameters regulate the behaviour of equations describing temporal and spatial changes of model state variables and their interactions. Generally, there is some uncertainty associated with each parameter. Model calibration is performed by comparing observed with predicted data and it is a crucial phase in the modelling process. It's an iterative and interactive task in which, after each simulation, the "modeller" analyses the results and performs changes on one or more equation's parameters trying to tune the model. This "tuning" procedure is a hard and "tedious" work requiring a good understanding of the effects of different parameters over the available variables. Automatic calibration procedures, based on systematic and exhaustive generation of parameter vectors and using several convergence methods, are available but they require a large number of model runs and are, therefore, not applicable to very complex ecosystem models demanding large computational times.
arXiv.org Artificial Intelligence
Sep-9-2008
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