Compressive Strength Prediction via Gene Expression Programming (GEP) and Artificial Neural Network (ANN) for Concrete Containing RCA

• Published in: Buildings (Basel) Vol. 11; no. 8; p. 324
• Main Authors: Ahmad, Ayaz, Chaiyasarn, Krisada, Farooq, Furqan, Ahmad, Waqas, Suparp, Suniti, Aslam, Fahid
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.08.2021
• Subjects: Accuracy; Aggregates; Algorithms; artificial neural network; Artificial neural networks; cement; Civil engineering; Compressive strength; Computers; Concrete; Construction industry; Data points; Environmental risk; Error analysis; Gene expression; gene expression programming; Genetic algorithms; Learning algorithms; Learning theory; Machine learning; Mechanical properties; Mortars (material); Natural resources; Neural networks; Performance evaluation; Porous materials; Project engineering; Raw materials; recycled coarse aggregate; Root-mean-square errors; Sensitivity analysis; Software; Sustainable development

To minimize the environmental risks and for sustainable development, the utilization of recycled aggregate (RA) is gaining popularity all over the world. The use of recycled coarse aggregate (RCA) in concrete is an effective way to minimize environmental pollution. RCA does not gain more attraction...