Case-Based Reasoning Approach to Estimating the Strength of Sustainable Concrete

Choongwan Koo, Ruoyu Jin, Bo Li, Seung Hyun Cha, Dariusz Wanatowski

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish
JournalComputers and Concrete
Publication statusPublished - 30 Jul 2017


  • Sustainable concrete
  • Advanced case-based reasoning
  • Environmentally friendly concrete materials
  • Concrete 23 mixture design
  • Concrete strength prediction
  • Optimization process


Dive into the research topics of 'Case-Based Reasoning Approach to Estimating the Strength of Sustainable Concrete'. Together they form a unique fingerprint.

Cite this