Indirect Analysis of Concrete Slump Using Different Metaheuristic-Empowered Neural Processors

Hamed Safayenikoo (), Fatemeh Nejati and Moncef L. Nehdi ()
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Hamed Safayenikoo: Department of Civil Engineering, Chabahar Maritime University, Chabahar 9971778631, Iran
Fatemeh Nejati: Department of Art and Architecture, Faculty of Architecture, Khatam University, Tehran 1991633357, Iran
Moncef L. Nehdi: Department of Civil Engineering, McMaster University, Hamilton, ON L8S 4M6, Canada

Sustainability, 2022, vol. 14, issue 16, 1-16

Abstract: Estimating the mechanical parameters of concrete is significant towards achieving an efficient mixture design. This research deals with concrete slump analysis using novel integrated models. To this end, four wise metaheuristic techniques of biogeography-based optimization (BBO), salp swarm algorithm (SSA), moth-flame optimization (MFO), and wind driven optimization (WDO) are employed to optimize a popular member of the neural computing family, namely multilayer perceptron (MLP). Four predictive ensembles are constructed to analyze the relationship between concrete slump and seven concrete ingredients including cement, water, slag, fly ash, fine aggregate, superplasticizer, and coarse aggregate. After discovering the optimal complexities by sensitivity analysis, the results demonstrated that the combination of metaheuristic algorithms and neural methods can properly handle the early prediction of concrete slump. Moreover, referring to the calculated ranking scores (RSs), the BBO-MLP (RS = 21) came up as the most accurate model, followed by the MFO-MLP (RS = 17), SSA-MLP (RS = 12), and WDO-MLP (RS = 10). Lastly, the suggested models can be promising substitutes to traditional approaches in approximating the concrete slump.

Keywords: sustainable construction; concrete mixture; slump; neural computing; metaheuristic optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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