The Role of Machine Learning in Predicting Project Delays
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V6I4P130Keywords:
Machine Learning, Project Delays, Construction Management, Primavera P6, Predictive Analytics, Risk MitigationAbstract
Cost overruns and stakeholder disputes are caused by delays in construction projects. This technique is employed in this research for delay forecasting and remediation of the project's progress through ML and integrated with project scheduling software Primavera P6. ML algorithms can analyze historical project data to find delay patterns before they actually happen. The results presented in this paper demonstrate that the delay prediction using the ML models trained on the Primavera P6 dataset is accurate 83 percent of the time and thus represents a way to enhance project risk management and performance.
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