A fusion of neural, genetic and ensemble machine learning approaches for enhancing the engineering predictive capabilities of lightweight foamed reinforced concrete beam

• Main Authors: Chen, Yang, Zeng, Jie, Jia, Jianping, Jabli, Mahjoub, Abdullah, Nermeen, Elattar, Samia, Khadimallah, Mohamed Amine, Marzouki, Riadh, Hashmi, Ahmed, Assilzadeh, Hamid
• Format: Article
• Published: Elsevier 2024
• Subjects: QD Chemistry; TA Engineering (General). Civil engineering (General); TP Chemical technology
• Online Access: http://eprints.um.edu.my/45259/; https://doi.org/10.1016/j.powtec.2024.119680

This research explores lightweight foamed reinforced concrete beams, crucial in modern construction for their strength and reduced weight. It introduces a novel approach, integrating three machine learning models: Neural Networks (NNs), Genetic Algorithms (GAs), and Ensemble Techniques, especially G...