AI-Powered Predictive Modeling: Revolutionizing Construction Risk

With the global construction market expected to expand substantially in the coming years and AI playing a crucial role in boosting productivity, this study aims to provide insights into the potential benefits of using AI for risk assessment in construction projects. Risk assessment is a critical and vital aspect of building project management. Effective risk identification, evaluation, and management are necessary to prevent time and cost overruns and to ensure project success. Existing risk assessment methods often fall short in understanding the complex and interdependent nature of risks in construction projects, especially under significant uncertainty. AI-based techniques provide innovative solutions by integrating various methods such as neural networks, genetic algorithms, fuzzy logic, and object-oriented approaches. These techniques often address risk interdependencies and significantly enhance the accuracy of risk assessments. In this article, we generate a synthetic dataset, train a Random Forest classifier to predict risks based on various project features, and evaluate the model's performance for accurate risk assessment in construction projects. The results demonstrate the effectiveness of employing AI, particularly Random Forest classifiers, for precise risk assessment in construction projects.

کلیدواژه ها:

Artificial intelligence (AI) ، Construction Risk Management ، Construction industry ، Project schedules ، Random Forest Classifier