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Computers and Concrete Volume 4, Number 4, August 2007 , pages 299-316 DOI: https://doi.org/10.12989/cac.2007.4.4.299 |
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Application of support vector regression for the prediction of concrete strength |
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Jong Jae Lee, Doo Kie Kim, Seong Kyu Chang and Jang-Ho Lee
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| Abstract | ||
| The compressive strength of concrete is a commonly used criterion in producing concrete. However, the test on the compressive strength is complicated and time-consuming. More importantly, since the test is usually performed 28 days after the placement of the concrete at the construction site, it is too late to make improvements if unsatisfactory test results are incurred. Therefore, an accurate and practical strength estimation method that can be used before the placement of concrete is highly desirable. In this study, the estimation of the concrete strength is performed using support vector regression (SVR) based on the mix proportion data from two ready-mixed concrete companies. The estimation performance of the SVR is then compared with that of neural network (NN). The SVR method has been found to be very efficient in estimation accuracy as well as computation time, and very practical in terms of training rather than the explicit regression analyses and the NN techniques. | ||
| Key Words | ||
| concrete strength; strength prediction; support vector regression (SVR); concrete mix proportion data; kernel function. | ||
| Address | ||
| Jong Jae Lee; Department of Civil and Environmental Engineering, Sejong University, Seoul 143-747, Korea Doo Kie Kim and Seong Kyu Chang; Department of Civil and Environmental Engineering, Kunsan National University, Kunsan, Jeonbuk 573-701, Korea Jang-Ho Lee; Department of Mechanical Engineering, Kunsan National University, Kunsan, Jeonbuk 573-701, Korea | ||