Hamilton (Chen), Serena; Pollino, Carmel
Bayesian networks (BNs) are simple graphical causal models that have been applied in a diverse range of fields. They were first conceived in the 1980s at the interface between artificial intelligence, expert systems and statistics, to deal with problems of reasoning and decision making under uncertainty. They have served many purposes including diagnosis, prediction, simulation and analysis, and are particularly suited to problems involving causality with inherent uncertainty. In environmental...[Show more]
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