Predictive models in machine learning for strength and life cycle assessment of concrete structures

Abstract

The integration of emerging technologies into the construction industry is crucial for the successful execution of technologically sophisticated initiatives. Multiple disciplines of Artificial Intelligence (AI) have undergone advancements in recent times, encompassing automation and prediction. Machine learning (ML), a subset of AI, has been predominantly applied to the domain of prediction. Hence, the focus of this review is on numerous machine learning techniques applied in the mechanical evaluation of concrete. Additionally, the whole life cycle of concrete is examined to promote sustainable practices that minimize negative environmental impacts. The evaluation further examines the challenges and prospective advancements of AI within the construction sector, considering the increasing reliance on technological improvement in the next decades. Hence, the review presents an in-depth analysis of viable machine learning models that optimize for certain strength components to improve the model's performance and accuracy.