Machine learning methods in analysis of concrete: a state-of-the-art review

Abstract

Machine learning application have permeated many facets of the society including civil engineering. It is used to predict and analyze various scenarios that were hitherto out of the reach of the human experts. In this paper, we aim to review the current state-of-the-art in machine learning applications related to design, compression strength, and fault detection aspect of concrete material. We identify the most relevant works and describe the strengths and weaknesses of each approach as well as provide recommendations for improvement.