ABSTRACT
The book continues with Bayesian mathematics merged with the information networks because they allow us not only to define the probability of a hazard occurring but also encapsulate risk more fully by integrating the probability of an accident given any particular hazard (Luxhøj 2002). Further than this, by integrating the information network theory, the restrictiveness of this approach to hazards and accidents can be removed. Analysis can occur based on the deeper level of information nodes, meaning the analysis can occur regardless of perceived blame, linear cause or even a negative outcome. Bayesian networks have been developed to indicate relationships within a system just as an information network does – therefore together these two methods have the potential to be a strong analytical tool.
