Hybrid machine learning for predicting strength of sustainable concrete
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METHODOLOGIES AND APPLICATION
Hybrid machine learning for predicting strength of sustainable concrete Anh-Duc Pham1 • Ngoc-Tri Ngo1
•
Quang-Trung Nguyen1 • Ngoc-Son Truong1
Ó Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Foamed concrete material is a sustainable material which is widely used in the construction industry due to their sustainability. Accurate prediction of their compressive strength is vital for structural design. However, empirical methods are limited to consider simultaneously all influencing factors in predicting the compressive strength of foamed concrete materials. Thus, this study proposed a novel hybrid artificial intelligence (AI) model which couples the least squares support vector regression (LSSVR) with the grey wolf optimization (GWO) to consider effectively the influencing factors and improve the predictive accuracy in predicting the foamed concrete’s compressive strength. Performance of the proposed model was evaluated using a real-world dataset. Comparison results confirm that the proposed GWO–LSSVR model was superior than the support vector regression, artificial neural networks, random forest, and M5Rules with the improvement rate of 144.2–284.0% in mean absolute percentage error (MAPE). Notably, the evaluation results show that the GWO–LSSVR model showed the good agreement between the actual and predicted values with the correlation coefficient of 0.991 and MAPE of 3.54%. Thus, the proposed AI model was suggested as an effective tool for designing foamed concrete materials. Keywords Artificial intelligence Machine learning Optimization Lightweight foamed concrete Sustainable concrete Compressive strength
1 Introduction The lightweight foamed concrete material is considered as a sustainable construction material that made of cementitious binders with void space, with or without fine aggregates. Compared with normal concretes, lightweight concrete materials have a low value of density, low thermal conductivity, high fire resistance, and high sound insulation capacity (Sayadi et al. 2016). Thus, they have been widely used in the construction field such as in geotechnical engineering, heat insulation, and roofs (Hajimohammadi et al. 2018; Nguyen et al. 2017). In addition, structural lightweight concretes can improve the sustainability and
Communicated by V. Loia. & Ngoc-Tri Ngo [email protected] 1
Faculty of Project Management, The University of Danang – University of Science and Technology, Danang City, Vietnam
reduce the damage probability by the earthquake. In practice, accurately determining their mechanical properties is important to evaluate the workability. Among mechanical properties, the compressive strength is crucial in foamed concretes (Nguyen et al. 2017). Therefore, this study concerns with a prediction of the foamed concrete’s compressive strength at the early stage which is vital in designing mixture proportions of foamed concrete. In the last decades, some empirical methods have been p
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