Continuing from previous studies of sustainable concrete containing environmentally friendly materials and existing modeling approach to predicting concrete properties, this study developed an estimation methodology to predicting the strength of sustainable concrete using an advanced case-based reasoning approach. It was conducted in two steps: (i) establishment of a case database and (ii) development of an advanced case-based reasoning model. Through the experimental studies, a total of 144 observations for concrete compressive strength and tensile strength were established to develop the estimation model. As a result, the prediction accuracy of the A-CBR model (i.e., 95.214% for compressive strength and 92.448% for tensile strength) performed superior to other conventional methodologies (e.g., basic case-based reasoning and artificial neural network models). The developed methodology provides an alternative approach in predicting concrete properties and could be further extended to the future research area in durability of sustainable concrete.
- Sustainable concrete
- Advanced case-based reasoning
- Environmentally friendly concrete materials
- Concrete 23 mixture design
- Concrete strength prediction
- Optimization process
Koo, C., Jin, R., Li, B., Cha, S. H., & Wanatowski, D. (2017). Case-Based Reasoning Approach to Estimating the Strength of Sustainable Concrete. Computers and Concrete. https://doi.org/10.12989/cac.2017.20.6.645