Risk prediction of project scheduling based cloud model

In project scheduling management, cloud operation and cloud model are introduced for a better consideration of both randomicity and fuzziness in project scheduling, as well as their relationship, giving us a clearer view of uncertainty in the project. Traditional methods, like probability statistics analysis and fuzzy mathematics, focus on their respective fields, that is, the former attaches more importance on randomicity while the latter considers fuzziness only. Based on the normal cloud model of project optimal scheduling, we have calculated the certainty index of completion probability and completion risk, and also made a relative analysis of randomicity and fuzziness, so that more information is provided for project management and decision.