Novel machine learning applications on fly ash based concrete: An overview

Abstract

A machine learning technique provides rapid access to various information models, approaches, complex systems, and algorithms. In the present scenario the artificial neural network, multiple linear regression, support vector machine, water cycle algorithm, and linear regression have much accessible. Continuously advancements of these techniques become a high impact on civil engineering, especially for the construction and infrastructure sector. In the present study, the historical perspective of research and development and application of machine learning techniques on fly ash-based concrete is presented. The models, algorithms, and approaches developed for predicting engineering properties of fly ash-based concrete were also discussed. These predictions using machine learning techniques have been much impacted on fly ash utilization in concrete. The utilization of fly ash in concrete also has revolutionary impacts on the environment and human health in the future. Machine learning is a useful and powerful technique that can predict concrete engineering properties and represent the scientific challenge in the construction and infrastructure sectors.