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Decision support techniques

Forest models: Models for describing the state change of forests (output)
Ecological models: Models for the describing the ecological phenomena (output)
Social models: historical and cultural values, values due to peace and quiet, aesthetic values, values due to recreational activities, values due to sports activities, values due to game management, values due to welfare effects, ethical values (output)
Other models: Other models used
MCDM methods: Type of Multi-criteria decision making techniques implemented, if any
Optimisation package: Product name of the optimisation package integrated, if any
Optimisation algorithm: Type of Optimisation algorithm have been implemented, if any
Risk evaluation:
Uncertainty evaluation: Approaches in communicating the uncertainty: uncertainty not considered, conventional approaches to statistics where the scientific uncertainty is considered as the frequentist probability, i.e. the chance of some observable event occuring if some particular hypothesis is assumed to be true and if the experiment was to be repeated indefinetely (or frequently), Monte Carlo simulations and bootstraping (use Frequentist statistical framework and interprets the distributions as sampling distributions for the estimates obtained and not as probability distributions for the actual quantities uderlying the estimates), Bayesian inference (conveys a strength of belief in a number between 0 and 1 or weight of evidence for some particular conjecture or hypothesis, e.g. Expectation maximisation (EM) algorithm
Planning scenario: Does the system support scenario creation? Is the historic data of prior scenarios easily available? Does it support what-if analysis?
Other methods (name of the detail wiki page): Other methods used

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