Modeling a Hybrid Early Warning System for complex and large projects

Any complex large-scale industrial project in the transnational environment especially those which activate within the development of new industrial technologies is a risk in itself since it is always a pioneer and has not the necessary back experience to predict the future. The originality of the practical contribution of this study consists in modeling setting and simulating with Bayesian Networks (RBs) an Early Warning Hybrid System which had as a goal the development of a conditional probability map in real time and an array of different early warning scenarios for managers of complex large-scale industrial projects in the transnational environment based on estimates of time and cost parameters.