Communicating physics-based wave model predictions of coral reefs using Bayesian belief networks

摘要: Abstract The use of physics-based wave propagation predictions requires a considerable time commitment, high level expertise and extensive climate reef data that are not always available when undertaking planning for management coasts coral ecosystems. Bayesian belief networks (BBNs) have at least three attributes make them an excellent choice to communicate model predictions. First, BBNs subsume thousands provide probabilistic outcomes. Second, by using prior probabilities, practitioner can still obtain outcomes even their knowledge input parameters is incomplete. Third, propagate evidence from outputs inputs, which be used identify conditions most likely deliver chosen outcome. These tested found hold BBN developed this purpose.