Non-linear and mixed regression models in predicting sustainable concrete strength
Journal article
Jin, R, Chen, Q and Soboyejo, A (2018). Non-linear and mixed regression models in predicting sustainable concrete strength. Construction and Building Materials. 170, pp. 142-152. https://doi.org/10.1016/j.conbuildmat.2018.03.063
| Authors | Jin, R, Chen, Q and Soboyejo, A |
|---|---|
| Abstract | Most previous research adopting the regression analysis to capture the relationship between concrete properties and mixture-design-related variables was based on the linear approach with limited accuracy. This study applies non-linear and mixed regression analyses to model properties of environmentally friendly concrete based on a comprehensive set of variables containing alternative or waste materials. It was found that best-fit non-linear and mixed models achieved similar accuracies and superior R2 values compared to the linear approach, with both the numerical and relative input methods. Individual materials’ effects on concrete strength were statistically quantified at different curing ages using the best-fit models. |
| Keywords | Sustainable concrete; Waste materials; Concrete mixture design; Cementitious materials; Predictive modeling; Non-linear regression analysis; Mixed model; Concrete strength |
| Year | 2018 |
| Journal | Construction and Building Materials |
| Journal citation | 170, pp. 142-152 |
| Publisher | Elsevier BV |
| ISSN | 0950-0618 |
| Digital Object Identifier (DOI) | https://doi.org/10.1016/j.conbuildmat.2018.03.063 |
| Publication dates | |
| May 2018 | |
| 23 Mar 2018 | |
| Publication process dates | |
| Accepted | 06 Mar 2018 |
| Deposited | 04 Jun 2020 |
| Accepted author manuscript | License File Access Level Open |
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