2023
DOI: 10.3389/fmats.2023.1159079
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Development of hybrid SVM-FA, DT-FA and MLR-FA models to predict the flexural strength (FS) of recycled concrete

Abstract: Recycled concrete from construction waste used as road material is a current sustainable approach. To provide feasible suggestions for civil engineers to prepare recycled concrete with high flexural strength (FS) for the road pavement, the present study proposed three hybrid machine learning models by combining support vector machine (SVM), decision tree (DT) and multiple linear regression (MLR) with the firefly algorithm (FA) for the computational optimization, named as SVM-FA, DT-FA, and MLR-FA, respectively… Show more

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References 58 publications
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“…Chiya et al [ 30 ] used the curing time of cement paste, water-binder ratio, and the content of microsilica and nanosilica as inputs to predict the mechanical properties of cement paste by constructing a multiple linear regression (MLR) model. Wang et al [ 31 ] used an improved MLR based on Firefly Algorithm (FA) to predict the flexural strength of recycled concrete. After considering nine kinds of concrete preparation parameters, a good regression model was obtained.…”
Section: Introductionmentioning
confidence: 99%
“…Chiya et al [ 30 ] used the curing time of cement paste, water-binder ratio, and the content of microsilica and nanosilica as inputs to predict the mechanical properties of cement paste by constructing a multiple linear regression (MLR) model. Wang et al [ 31 ] used an improved MLR based on Firefly Algorithm (FA) to predict the flexural strength of recycled concrete. After considering nine kinds of concrete preparation parameters, a good regression model was obtained.…”
Section: Introductionmentioning
confidence: 99%