Innovative machine learning approaches to predict the compressive strength of recycled plastic aggregate self-compacting concrete incorporating different waste ashes

Compressive strength and microstructural characteristics of class C fly ash geopolymer

Xiaolu Guo, Huisheng Shi, Warren A. Dick · Cement and Concrete Composites · 2009 · 810 citations

Natural Sciences, Materials Engineering, Materials Science +12

Prediction of compressive strength of recycled aggregate concrete using artificial neural networks

Zhenhua Duan, Shi-Cong Kou, Chi Sun Poon · Construction and Building Materials · 2012 · 495 citations

Architecture, Civil Engineering, Materials Engineering +16

Predictive modeling for sustainable high-performance concrete from industrial wastes: A comparison and optimization of models using ensemble learners

Furqan Farooq, Wisal Ahmed, Arslan Akbar et al. · Journal of Cleaner Production · 2021 · 406 citations

Computing, Environmental Engineering, Materials Engineering +15

A novel hybrid extreme learning machine–grey wolf optimizer (ELM-GWO) model to predict compressive strength of concrete with partial replacements for cement

Mahdi Shariati, Mohammad Saeed Mafipour, Behzad Ghahremani et al. · Engineering With Computers · 2020 · 356 citations

Engineering, Civil Engineering, Materials Engineering +14

Development of high-performance self-compacting concrete using waste recycled concrete aggregates and rubber granules

Farhad Aslani, Guowei Ma, Dominic Law Yim Wan et al. · Journal of Cleaner Production · 2018 · 331 citations

Engineering, Civil Engineering, Materials Engineering +16