Bayesian networks as a resilience tool for decision-making processes in uncertainty conditions
Project management through process technologies has taken on a key role in recent decades as a planning and control tool for building processes. However, a wide divergence between expectations and results emerges from the available literature. The existing tools, behind apparent efficiency, proved to be inadequate, detached from practical reality and unable to handle complexity. The processes that govern the buildings in fact must be related to a turbulent and complex context that leads to uncertainty of process and outcomes. The research carried out aims to strengthen the existing tools, through the development and testing of new tools that can rigorously and objectively govern the risk and the uncertainty of the construction sector.
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