Modelo estocástico preditivo para controle de custos em obras de infraestrutura

Price change orders in infrastructure projects represent significant challenges to the success of large-scale endeavors in both public and private sectors. This study proposes a predictive stochastic model to improve cost forecasting and control in construction projects, thereby mitigating financial risks in large-scale infrastructure development. The model employs advanced mathematical formulations based on birth-and-death stochastic processes and Artificial Intelligence (AI) techniques for time-series clustering, providing optimistic, neutral, and pessimistic scenarios to guide decision-making in project management. By integrating stochastic methods with AI, the proposed approach offers a robust framework for managing the inherent uncertainties of construction projects, thereby enhancing budget reliability and financial oversight.